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`____________________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`____________________
`
`SAMSUNG ELECTRONICS CO., LTD.; and
`SAMSUNG ELECTRONICS AMERICA, INC.
`Petitioners
`
`v.
`
`IMAGE PROCESSING TECHNOLOGIES, LLC
`Patent Owner
`
`____________________
`
`Patent No. 8,989,445
`____________________
`
`DECLARATION OF DR. JOHN C. HART
`IN SUPPORT OF PETITION FOR INTER PARTES REVIEW
`OF U.S. PATENT NO. 8,989,445
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`TABLE OF CONTENTS
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`INTRODUCTION .............................................................................................................. 1
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`BACKGROUND AND EXPERIENCE ............................................................................. 1
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`A.
`
`B.
`
`Qualifications .......................................................................................................... 1
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`Previous Testimony ................................................................................................ 4
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`TECHNOLOGICAL BACKGROUND.............................................................................. 5
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`THE ’445 Patent ............................................................................................................... 11
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`SUMMARY OF OPINIONS ............................................................................................ 21
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`LEVEL OF ORDINARY SKILL IN THE ART .............................................................. 22
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`
`I.
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`II.
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`III.
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`IV.
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`V.
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`VI.
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`VII. CLAIM CONSTRUCTION .............................................................................................. 23
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`VIII. THE PRIOR ART TEACHES OR SUGGESTS EVERY STEP AND FEATURE
`OF THE CHALLENGED CLAIMS OF THE ’445 PATENT ......................................... 23
`
`A.
`
`Overview Of The Prior Art References ................................................................ 23
`
`1.
`
`2.
`
`3.
`
`4.
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`Alton L. Gilbert et al., A Real-Time Video Tracking System,
`PAMI-2 No. 1 IEEE Transactions on Pattern Analysis and
`Machine Intelligence 47 (Jan. 1980) (“Gilbert”) (Ex. 1005) .................... 23
`
`U.S. Patent No. 5,521,843 (“Hashima”) (Ex. 1006) ................................. 32
`
`U.S. Patent No. 5,761,326 (“Brady”) (Ex. 1007) .................................... 41
`
`O. D. Altan et al., “Computer Architecture And Implementation Of
`Vision-Based Real-Time Lane Sensing,” Proceedings Of The
`Intelligent Vehicles ’92 Symposium 202 (1992) (“Altan”) (Ex.
`1008) ......................................................................................................... 51
`
`B.
`
`Ground 1: Gilbert In View Of Brady Teaches Or Suggests Every Step
`And Feature Of The Challenged Claims .......................................................... 52
`
`1.
`
`2.
`
`3.
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`4.
`
`Reasons To Combine Gilbert And Brady ............................................. 52
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`Claim 1 ..................................................................................................... 56
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`Claim 4 ...................................................................................................... 65
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`Claim 6 ...................................................................................................... 67
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`Claim 9 ...................................................................................................... 68
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`Claim 18 .................................................................................................... 72
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`Claim 24 .................................................................................................... 74
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`Claim 25 .................................................................................................... 78
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`Claim 27 .................................................................................................... 78
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`5.
`
`6.
`
`7.
`
`8.
`
`9.
`
`10.
`
`Detailed Application Of Gilbert, Brady, And Altan To The
`Challenged Claims .................................................................................... 78
`
`C.
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`Ground 2: Hashima In View Of Gilbert Teaches Or Suggests Every
`Step And Feature Of The Challenged Claims ................................................ 111
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`1.
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`2.
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`3.
`
`4.
`
`5.
`
`6.
`
`7.
`
`8.
`
`9.
`
`Reasons To Combine Hashima And Gilbert ...................................... 112
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`Claim 1 ................................................................................................... 115
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`Claim 4 .................................................................................................... 123
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`Claim 6 .................................................................................................... 125
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`Claim 9 .................................................................................................... 126
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`Claim 18 .................................................................................................. 129
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`Claim 24 .................................................................................................. 130
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`Claim 25 .................................................................................................. 133
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`Claim 27 .................................................................................................. 133
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`10.
`
`Detailed Application Of Hashima, Gilbert, And Altan To The
`Challenged Claims .................................................................................. 134
`
`D.
`
`Ground 3: Hashima In View Of Brady Teaches Or Suggests Every Step
`And Feature Of The Challenged Claims ............................................................. 181
`
`1.
`
`2.
`
`3.
`
`4.
`
`5.
`
`Reasons To Combine Hashima And Brady ........................................ 181
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`Claim 1 ................................................................................................... 185
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`Claim 4 .................................................................................................... 190
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`Claim 6 .................................................................................................... 191
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`Claim 9 .................................................................................................... 192
`ii
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`Claim 18 .................................................................................................. 196
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`Claim 24 .................................................................................................. 197
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`Claim 25 .................................................................................................. 200
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`Claim 27 .................................................................................................. 200
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`Detailed Application Of Hashima, Brady, And Altan To The
`Challenged Claims .................................................................................. 200
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`6.
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`7.
`
`8.
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`9.
`
`10.
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`IX.
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`CONCLUSION ............................................................................................................... 245
`
`iii
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`I, John C. Hart, declare as follows:`
`
`1.
`
`I.
`
`INTRODUCTION
`2.
`
`I have been retained by Samsung Electronics Co., Ltd. and Samsung
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`Electronics America, Inc. (collectively, “Petitioner”) as an independent expert
`
`consultant in this proceeding before the United States Patent and Trademark Office
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`(“PTO”).
`
`3.
`
`I have been asked to consider whether certain references teach or
`
`suggest the features recited in Claims 1, 4, 6, 9, 18, 24, 25, and 27 (the
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`“Challenged Claims”) of U.S. Patent No. 8,989,445 (“the ’445 Patent”) (Ex. 1001),
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`which I understand is allegedly owned by Image Processing Technologies, LLC
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`(“Patent Owner”). My opinions and the bases for my opinions are set forth below.
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`4.
`
`I am being compensated at my ordinary and customary consulting rate
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`for my work.
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`5. My compensation is in no way contingent on the nature of my
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`findings, the presentation of my findings in testimony, or the outcome of this or
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`any other proceeding. I have no other interest in this proceeding.
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`II. BACKGROUND AND EXPERIENCE
`A. Qualifications
`6.
`I have more than 25 years of experience in computer graphics and
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`image processing technologies. In particular, I have devoted much of my career to
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`researching and designing graphics hardware and systems for a wide range of
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`applications.
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`7. My research has resulted in the publication of more than 80 peer-
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`reviewed scientific articles, and more than 50 invited papers, and talks in the area
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`of computer graphics and image processing.
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`8.
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`I have authored or co-authored several publications that are directly
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`related to target identification and tracking in image processing systems. Some
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`recent publications include:
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`•
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`•
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`•
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`P.R. Khorrami, V.V. Le, J.C. Hart, T.S. Huang. A System for
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`Monitoring the Engagement of Remote Online Students using Eye
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`Gaze Estimation. Proc. IEEE ICME Workshop on Emerging
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`Multimedia Systems and Applications, July 2014.
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`V. Lu, I. Endres, M. Stroila and J.C. Hart. Accelerating Arrays of
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`Linear Classifiers Using Approximate Range Queries. Proc. Winter
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`Conference on Applications of Computer Vision, Mar. 2014.
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`M. Kamali, E. Ofek, F. Iandola, I. Omer, J.C. Hart Linear Clutter
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`Removal from Urban Panoramas. Proc. International Symposium on
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`Visual Computing. Sep. 2011.
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`9.
`
`From 2008-2012, as a Co-PI of the $18M Intel/Microsoft Universal
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`Parallelism Computing Research Center at the University of Illinois, I led the
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`AvaScholar project for visual processing of images that included face
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`identification, tracking and image histograms.
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`10.
`
`11.
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`I am a co-inventor of U.S. Patent No. 7,365,744.
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`I have served as the Director for Graduate Studies for the Department
`
`of Computer Science, an Associate Dean for the Graduate College, and I am
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`currently serving as the Executive Associate Dean of the Graduate College at the
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`University of Illinois. I am also a professor in the Department of Computer
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`Science at the University of Illinois, where I have served on the faculty since
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`August 2000. As a professor I have taught classes on image processing and
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`graphics technology and have conducted research into specific applications of
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`these technologies.
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`12. From 1992 to 2000, I worked first as an Assistant Professor and then
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`as an Associate Professor in the School of Electrical Engineering and Computer
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`Science at Washington State University.
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`13. From 1991-1992, I was a Postdoctoral Research Associate at the
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`Electronic Visualization Laboratory at the University of Illinois at Chicago, and at
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`the National Center for Supercomputing Applications at the University of Illinois
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`at Urbana-Champaign.
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`14.
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`I earned a Doctor of Philosophy in Electrical Engineering and
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`Computer Science from the University of Illinois at Chicago in 1991.
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`I earned a Master’s Degree in Electrical Engineering and Computer
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`15.
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`Science from the University of Illinois at Chicago in 1989.
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`16.
`
`I earned a Bachelor of Science in Computer Science from Aurora
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`University in 1987.
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`17.
`
`I have been an expert in the field of graphics and image processing
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`since prior to 1996. I am qualified to provide an opinion as to what a person of
`
`ordinary skill in the art (“POSA”) would have understood, known, or concluded as
`
`of 1996.
`
`18. Additional qualifications are detailed in my curriculum vitae, which I
`
`understand has been submitted as Exhibit 1003 in this proceeding.
`
`B.
`19.
`
`Previous Testimony
`
`In the previous five years, I have testified as an expert at trial or by
`
`deposition or have submitted declarations in the following cases:
`
`20. Certain Computing or Graphics Systems, Components Thereof, and
`
`Vehicles Containing Same, Inv. No. 337-TA-984.
`
`21. ZiiLabs Inc., Ltd v. Samsung Electronics Co. Ltd. et al., No. 2:14-cv-
`
`00203 (E.D. Tex. Feb. 4, 2016).
`
`22. Certain Consumer Electronics with Display and Processing
`
`Capabilities, Inv. No. 337-TA-884.
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`III. TECHNOLOGICAL BACKGROUND
`23.
`Image processing systems have long used histograms as a
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`mathematical tool to identify and track image features and to adjust image
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`properties. The use of histograms to identify and track image features dates back
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`to well before 1997. D. Trier, A. K. Jain and T. Taxt, “Feature Extraction Methods
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`for Character Recognition-A Survey”, Pattern Recognition, vol. 29, no. 4, 1996,
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`pp. 641–662 (Ex. 1009) (citing M. H. Glauberman, “Character recognition for
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`business machines,” Electronics, vol. 29, pp. 132(136), Feb. 1956(Ex. 1010))
`
`24. A digital image is represented by a number of picture elements, or
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`pixels, where each pixel has certain properties, such as brightness, color, position,
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`velocity, etc., which may be referred to as domains. For each pixel property or
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`domain, a histogram may be formed. A histogram is a specific type of bar chart
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`used for counting the number of items meeting certain criteria. In image
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`processing, histograms count the number of pixels in the image having certain
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`characteristics, where each bar counts the pixels that share a specific value or value
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`range of that characteristic. For example, if the luminance (brightness) of each
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`pixel were represented by an 8-bit value, a luminance histogram would be a bar
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`chart of the number of pixels in the image indicating, for each luminance value
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`from 0 to 255, the count of the number of pixels in the image with that luminance
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`value. As shown below, a luminance histogram may reveal certain properties of an
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`image, such as whether it is properly exposed, based on whether an excessive
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`number of pixels fall on the dark end or light end of the luminance range.
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`
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`25. Histograms of other pixel properties can also be formed. For
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`example, the figure below illustrates two histograms formed by counting the
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`number of black pixels having each X-coordinate value (i.e., the X-coordinate
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`domain) and the number having each Y-coordinate value (i.e., the Y-coordinate
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`domain).
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
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`26. Such histograms are sometimes called “projection histograms”
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`because they represent the image projected onto each axis. In the example above,
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`the image was pure black and white, but projection histograms of a greyscale
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`image can also be formed in a similar manner by defining a luminance threshold
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`and projecting, for example, only those pixels that have a luminance value lower
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`than 100.
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`27. A more complex greyscale image is shown below, along with its
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`luminance histogram (black = 0; white = 255):
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
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`28. Here, the peak in the dark luminance region (luminance = 0-50)
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`corresponds to the dark suit and tie and relatively dark background. The peak in
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`the light luminance region (luminance > 230) corresponds to the white shirt, while
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`the central peak (between luminance 130 and 170) corresponds largely to the
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`medium brightness of the face. If one were to select only the subset of pixels with
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`brightness between 130 and 170 and plot them according to their x and y position,
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`one would get the following image:
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`
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`29. Taking projection histograms of this subset of pixels with luminance
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`between 130 and 170, then, provides an indication of location of the face in the
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`image. On the left, below, is a projection of this subset of pixels onto the x axis,
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`and on the right is a similar projection onto the y axis.
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
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`30. Histograms may also be formed of pixel color properties in much the
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`same way. Color is typically represented by three values: hue, saturation and
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`luminance. Hue (aka “tone”) is an angle ranging from 0° to 360° around a color
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`wheel that indicates which “color” is bring represented, e.g. 0° = red, 60° = yellow,
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`120° = green, 180° = cyan, 240° = blue, and 300° = magenta. Saturation, which
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`may also range from 0 to 255, represents how “brilliant” the color is. For example,
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`if a color with a saturation of 255 represents red, then a saturation of 128 would
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`represent pink and a saturation of 0 would represent gray. Luminance ranges from
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`0 to 255 and represents the “brightness” of the color. If luminance = 0, then the
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`color is black, regardless of the other values. Given a color image, the luminance
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`values of the pixels would yield the “black-and-white” or grayscale version of the
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`image.
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
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`IV. THE ’445 Patent
`31. The ’445 Patent, entitled “Image Processing Apparatus And Method,”
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`was filed on August 13, 2014, and issued on March 24, 2015. The ’445 Patent
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`names Patrick Pirim as the sole inventor. I understand that the ’445 Patent claims
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`a priority date of July 22, 1996.
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`32. The ’445 Patent is generally directed to tracking a target using an
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`image processing system. For example, in the Abstract, the ’445 Patent notes that
`
`the invention relates to “[a] method and apparatus for localizing an area in relative
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`movement and for determining the speed and direction thereof.” Ex. 1001, ’445
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`Patent at Abstract.
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`33. The ’445 Patent uses the pixels in a frame of an image of a video
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`signal to form one or more histograms in order to identify and track a target. See
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`e.g., Ex. 1001, ’445 Patent at Claim 1. The input signal employed in the ’445
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`Patent is comprised of a “succession of frames, each frame having a succession of
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`pixels.” Ex. 1001 at 3:34-37. Although the disclosed embodiments relate
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`primarily to a video signal, the ’445 Patent also teaches that the input signal could
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`correspond to other types of signals, for example “ultrasound, IR, Radar, tactile
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`array, etc.” Ex. 1001, ’445 Patent at 9:29-34.
`
`34. The ’445 Patent teaches constructing a histogram showing the
`
`frequency of the pixels meeting a certain characteristic. In the ’445 Patent, these
`
`characteristics—such as luminance or speed—are referred to as “domains.”
`
`Histograms may be constructed in a variety of domains, for example, the ’445
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`Patent teaches that examples of possible domains include pixel data such as “i)
`
`luminance, ii) speed (V), iii) oriented direction (D1), (iv) time constant (CO), v)
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`hue, vi) saturation, and vii) first axis (x(m)), and viii) second axis (y(m)).” Id. at
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`4:9-13.
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`35. The histograms include a plurality of “classes” within a given
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`domain. Figure 14a (and the accompanying text) illustrates an example of
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`“classes” within a domain:
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
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`FIG. 14 a shows an example of the successive classes C1
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`C2 . . . Cn−1 Cn, each representing a particular velocity, for
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`a hypothetical velocity histogram, with their being
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`categorization for up to 16 velocities (15 are shown) in
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`this example. Also shown is envelope 38, which is a
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`smoothed representation of the histogram.
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`Ex. 1001, ’445 Patent at 20:51-56.
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`36. The hypothetical histogram in Figure 14a would be constructed using
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`histogram formation block 25 in Figure 11. In this figure, various histogram
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`processors (numbered 24-29) are shown that allow creation of histograms in
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`various domains. Block 25 is disclosed as creating velocity histograms. Id. at
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`17:7-13.
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
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`A detailed depiction of histogram block 25 is shown in Figure 13:
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`Inter Partes Review of U.S. Patent No. 8,989,445
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`37.
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`In Figure 13, velocity data for a pixel is input into a memory address
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`and into classifier 25b. The classifier contains registers 106 that correspond to
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`classes within the particular domain. Thus, for a classifier in a velocity histogram
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`formation block, the classifier would have a register for each velocity class.
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`Because the histogram will only be incremented for pixels satisfying the
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`classification criteria that, when met, outputs a classification signal of “1,” the
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`histogram in Figure 14a would be constructed using a classifier 25b that has each
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`of the velocity-class registers set to “1.” In this example, each pixel that is input
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`into classifier 25b would generate a classification signal of “1.” The histogram
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`would then be updated to include the input pixel, which it would do by
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`incrementing the histogram bin corresponding to the appropriate velocity class. In
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`other examples, a classifier may output a classification signal of “1” for only
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`specific classes of a domain, rather than for all of the classes in a domain as in
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`Figure 14a. Thus, for example, the classifier could choose pixels with only
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`specific velocities for consideration in subsequent histograms. This feature may be
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`used in conjunction with the output from other classification units to create
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`histograms identifying only pixels meeting multiple classification criteria in a
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`variety of domains.
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`38. The ’445 Patent discloses that its teachings are applicable to a broad
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`range of applications. For example, in one embodiment, the ’445 Patent performs
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`“automatic framing of a person . . . during a video conference.” Ex. 1001, ’445
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`Patent at 22:6-8. In this application, histograms are constructed in the X- and Y-
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`domains and count the number of pixels between successive frames where the
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`differences in luminance are above certain threshold values. Ex. 1001, ’445 Patent
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`at 22:47-57. By this method, the ’445 Patent teaches the system is able to
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`determine the boundaries of the target based on peaks in the histograms generated.
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`Ex. 1001, ’445 Patent at 10:35-63. This application and result are shown in Figure
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`16 and 17, reproduced below:
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
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`Ex. 1001, Fig. 16
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`Ex. 1001, Fig. 17
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`39. The system may use a mounted spotlight or camera to automatically
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`track a target, for example using a spotlight mounted on a helicopter to track a
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`target on the ground or using automated stage lights to track a performer during a
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`performance. Ex. 1001, ’445 Patent at 23:38-43. The ’445 Patent also teaches that
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`“[t]he invention would similarly be applicable to weapons targeting systems.” Ex.
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`1001, ’445 Patent at 23:42-43.
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`40.
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`In each of these embodiments, the ’445 Patent finds the X- and Y-
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`minima and maxima of the histograms and uses these points to determine a center
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`point of the target. The patent states that the “XMIN and XMAX” for the X-projection
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`histogram and “YMIN and YMAX” for the y projection histogram, are “key
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`characteristics” of the histogram “which include the minimum (MIN) of the
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`histogram” and “the maximum (MAX) of the histogram.” Id. at 19:43-50. It
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`teaches that these key characteristics are computed by the condition:
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`For each pixel with a validation signal V2 of “l”:
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`(a) if the data value of the pixel<MIN (which is initially
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`set to the maximum possible value of the histogram),
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`then write data value in MIN,
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`(b) if the data value of the pixel>MAX (which is initially
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`set to the minimum possible value of the histogram), then
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`write data value in MAX
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`Id. at 19:53-59. Hence the ‘445 Patent defines the minimum of the X-projection
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`histogram is the smallest X-coordinate of any pixel in the image region whose
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`validation signal is “1.” Similarly the maximum is the largest X-coordinate of any
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`pixel in the image region whose validation signal is “1.” The same holds true for
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`the Y-projection histogram where the maximum and minimum are computed in the
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`same way, but using the y coordinate axis.
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`41. After determining the X- and Y-minima and maxima of the
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`histograms, the ’445 Patent teaches that a center point of the target image may be
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`found at the coordinates of (XMIN+XMAX)/2 and (YMIN+YMAX)/2. Ex. 1001, ’445
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`Patent at 24:48-53. This is only one possible way of computing a center point of
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`an object. Indeed, for an irregularly shaped object like those shown in Figure 20,
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`below, there is not one clear center point. Rather, various center points such as
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`center of mass, center-of-area, and center of gravity might all give different
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`coordinates, but would nevertheless accomplish the purpose of the ’445 Patent.
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`42. Once the center of the target is determined, the center is used to adjust
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`the camera or spotlight to be directed to the moving target:
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`
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`Having acquired the target, controller 206 controls
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`servomotors 208 to maintain the center of the target in
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`the center of the image. . . .
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`It will be appreciated that as the target moves, the
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`targeting box will move with the target, constantly
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`adjusting the center of the targeting box based upon the
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`movement of the target, and enlarging and reducing the
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`size of the targeting box. The targeting box may be
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`displayed on monitor 212, or on another monitor as
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`desired to visually track the target.
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`Ex. 1001, ’445 Patent at 25:10-24.
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`43.
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`In addition, the ’445 Patent teaches that as part of the identification
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`and tracking process, the imaging system may place a tracking box around the
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`target that “may be displayed on monitor 212, or on another monitor as desired to
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`visually track the target.” Ex. 1001, ’445 Patent at 25:10-24. For example, Figure
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`23 shows an example of the tracking box in a frame:
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`
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`Ex. 1001 at Fig. 23
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`20
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`44. Although the ’445 Patent only teaches tracking a single target, or
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`selecting a single target from among multiple targets, it contemplates that its
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`methods may be adapted for tracking multiple targets simultaneously: “[W]hile the
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`invention has been described with respect to tracking a single target, it is foreseen
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`that multiple targets may be tracked, each with user-defined classification criteria,
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`by replicating the various elements of the invention.” Ex. 1001, ’445 Patent at
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`25:56-61.
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`V.
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`SUMMARY OF OPINIONS
`45.
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`In preparing this declaration, I have reviewed at least the documents
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`labeled Exhibits 1001-1011 and other materials referred to herein in connection
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`with providing this declaration. In addition to these materials, I have relied on my
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`education, experience, and my knowledge of practices and principles in the
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`relevant field, e.g., image processing. My opinions have also been guided by my
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`appreciation of how one of ordinary skill in the art would have understood the
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`claims and specification of the ’445 Patent around the time of the alleged
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`invention, which I have been asked to assume is the earliest claimed priority date
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`of July 22, 1996.
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`46. Based on my experience and expertise, it is my opinion that certain
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`references teach or suggest all the features recited in the Challenged Claims of the
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`’445 Patent, as explained in detail below. Specifically, it is my opinion that the
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`21
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`Challenged Claims are disclosed by Alton L. Gilbert et. al., A Real-Time Video
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`Tracking System (“Gilbert”) in combination with U.S. Patent No. 5,761,326
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`(“Brady”). It is also my opinion that the Challenged Claims are disclosed by U.S.
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`Patent No. 5,521,843 (“Hashima”) in combination with Gilbert. Finally, it is my
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`opinion that the Challenged Claims are disclosed by Hashima in combination with
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`Brady.
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`VI. LEVEL OF ORDINARY SKILL IN THE ART
`47. Based on my review of the ’445 Patent specification, claims, file
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`history, and prior art, I believe one of ordinary skill in the art around the time of
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`the alleged invention of the ’445 Patent would have had either (1) a Master’s
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`Degree in Electrical Engineering or Computer Science or the equivalent plus at
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`least a year of experience in the field of image processing, image recognition,
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`machine vision, or a related field or (2) a Bachelor’s Degree in Electrical
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`Engineering or Computer Science or the equivalent plus at least three years of
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`experience in the field of image processing, image recognition, machine vision, or
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`a related field. Additional education could substitute for work experience and vice
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`versa.
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`48.
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`In determining the level of ordinary skill in the art, I was asked to
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`consider, for example, the type of problems encountered in the art, prior art
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`solutions to those problems, the rapidity with which innovations are made, the
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`sophistication of the technology, and the educational level of active workers in the
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`field.
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`49. My opinions concerning the ’445 Patent claims are from the
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`perspective of a person of ordinary skill in the art (“POSA”), as set forth above.
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`VII. CLAIM CONSTRUCTION
`50. For my analysis of the ’445 Patent, I have interpreted all claim terms
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`according to their plain and ordinary meaning.
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`VIII. THE PRIOR ART TEACHES OR SUGGESTS EVERY STEP AND
`FEATURE OF THE CHALLENGED CLAIMS OF THE ’445 PATENT
`A. Overview Of The Prior Art References
`1.
`Alton L. Gilbert et al., A Real-Time Video Tracking System,
`PAMI-2 No. 1 IEEE Transactions on Pattern Analysis and
`Machine Intelligence 47 (Jan. 1980) (“Gilbert”) (Ex. 1005)
`51. Gilbert arose out of efforts by researchers at U.S. Army White Sands
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`Missile Range, New Mexico, in collaboration with New Mexico State University,
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`Las Cruces, who developed a system that utilizes histograms to identify and track
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`targets in flight such as rockets and aircraft. Gilbert was published in the January
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`1980 issue of IEEE Transactions on Pattern Analysis and Machine Intelligence, a
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`peer-reviewed journal published by the Institute of Electrical and Electronics
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`Engineers (“IEEE”). (Ex. 1011, Grenier Decl.)
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`52. Gilbert generally relates to “object identification and tracking
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`applications of pattern recognition at video rates.” Ex. 1005 at 47, Abstract.
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`23
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`Gilbert discloses “a system for missile and aircraft identification and tracking . . .
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`applied in real time to identify and track objects.” Ex.1005, Gilbert at 47. It
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`accomplishes this tracking by employing a series of processors, including an IO
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`processor, a video processor, a projection processor, a tracker processor, and a
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`control processor. Ex. 1005, Gilbert at 48. These elements are shown in Gilbert
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`Figure 1:
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`
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`Ex. 1005, Gilbert at 48. Each of these processors performs a different role in
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`identifying, locating, and ultimately tracking a target.
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`53. For example, the video processor receives a digitized video signal as
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`input that comprises 60 frames/s. Although Gilbert uses the word “field” instead
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`of “frame,” a POSA would have understood that a “frame” consists of two “fields”
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`
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`24
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`Declaration of Dr. John C. Hart
`Inter Partes Review of U.S. Patent No. 8,989,445
`in the context in which they are used in Gilbert. (At the time, video signals were
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`interlaced such that a frame of a non-interlaced video consisted of two fields. The
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`first field would be the odd numbered sca