UNITED STATES PATENT AND TRADEMARK OFFICE
`
`____________________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`____________________
`
`SAMSUNG ELECTRONICS CO., LTD.; AND
`SAMSUNG ELECTRONICS AMERICA, INC.
`Petitioner
`
`v.
`
`IMAGE PROCESSING TECHNOLOGIES, LLC
`Patent Owner
`
`____________________
`
`Patent No. 8,805,001
`____________________
`
`PETITION FOR INTER PARTES REVIEW
`OF U.S. PATENT NO. 8,805,001
`
`
`
`

`
`Petition for Inter Partes Review
`Patent No. 8,805,001
`
`
`
`I.
`
`TABLE OF CONTENTS
`
`Contents
`INTRODUCTION ........................................................................................... 1
`
`II. MANDATORY NOTICES UNDER 37 C.F.R. § 42.8 ................................... 1
`
`III.
`
`PAYMENT OF FEES UNDER 37 C.F.R. § 42.15(a) .................................... 2
`
`IV. GROUNDS FOR STANDING ........................................................................ 2
`
`V.
`
`PRECISE RELIEF REQUESTED .................................................................. 2
`
`VI. LEGAL STANDARDS ................................................................................... 3
`
`A.
`
`B.
`
`Claim Construction ............................................................................... 3
`
`Level Of Ordinary Skill In The Art ....................................................... 4
`
`VII. OVERVIEW OF THE RELEVANT TECHNOLOGY AND ’001
`PATENT .......................................................................................................... 4
`
`VIII. DETAILED EXPLANATION OF GROUNDS ............................................ 10
`
`A. Overview Of The Prior Art References .............................................. 10
`
`1.
`
`2.
`
`3.
`
`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) ............................................................. 10
`
`U.S. Patent No. 5,521,843 (“Hashima”) (Ex. 1006) .............. 19
`
`U.S. Patent No. 5,150,432 (“Ueno”) (Ex. 1007) ................... 26
`
`IX. Specific Explanation Of Grounds For Invalidity........................................... 32
`
`A. Ground 1: Gilbert In View Of Hashima Renders Obvious
`Claims 1-4 ........................................................................................... 32
`
`1.
`
`2.
`
`Reasons To Combine Gilbert And Hashima ............................ 32
`
`Claim 1 ...................................................................................... 37
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`Petition for Inter Partes Review
`Patent No. 8,805,001
`Claim 2: “The process according to claim 1, wherein
`identifying the target in said at least one histogram
`further comprises determining a center of the target to be
`between X and Y minima and maxima of the target” .............. 42
`
`Claim 3: “The process according to claim 1, wherein
`identifying the target in said at least one histogram
`further comprises determining the center of the target at
`regular intervals” ....................................................................... 43
`
`Claim 4: “The process according to claim 1 further
`comprising drawing a tracking box around the target” ............ 44
`
`Gilbert And Hashima Are Not Cumulative .............................. 46
`
`3.
`
`4.
`
`5.
`
`6.
`
`B.
`
`Ground 2: Hashima In View Of Ueno Renders Obvious
`Claims 1-4 ........................................................................................... 49
`
`1.
`
`2.
`
`3.
`
`4.
`
`5.
`
`6.
`
`Reasons To Combine Hashima And Ueno ............................... 49
`
`Claim 1 ...................................................................................... 51
`
`Claim 2: “The process according to claim 1, wherein
`identifying the target in said at least one histogram
`further comprises determining a center of the target to be
`between X and Y minima and maxima of the target” .............. 55
`
`Claim 3: “The process according to claim 1, wherein
`identifying the target in said at least one histogram
`further comprises determining the center of the target at
`regular intervals” ....................................................................... 55
`
`Claim 4: “The process according to claim 1 further
`comprising drawing a tracking box around the target” ............ 56
`
`Hashima And Ueno Are Not Cumulative ................................. 58
`
`C.
`
`Ground 3: Ueno In View Of Gilbert Renders Obvious Claims
`1-4 ........................................................................................................ 60
`
`1.
`
`2.
`
`Reasons To Combine Ueno And Gilbert .................................. 60
`
`Claim 1 ...................................................................................... 64
`
`
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`Petition for Inter Partes Review
`Patent No. 8,805,001
`Claim 2: “The process according to claim 1, wherein
`identifying the target in said at least one histogram
`further comprises determining a center of the target to be
`between X and Y minima and maxima of the target” .............. 68
`
`Claim 3: “The process according to claim 1, wherein
`identifying the target in said at least one histogram
`further comprises determining the center of the target at
`regular intervals” ....................................................................... 68
`
`Claim 4: “The process according to claim 1 further
`comprising drawing a tracking box around the target” ............ 69
`
`Ueno and Gilbert Are Not Cumulative ..................................... 72
`
`3.
`
`4.
`
`5.
`
`6.
`
`X.
`
`CONCLUSION .............................................................................................. 74
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`
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`Petition for Inter Partes Review
`Patent No. 8,805,001
`
`LIST OF EXHIBITS1
`
`U.S. Patent No. 8,805,001 (“the ’001 Patent”)
`Declaration of Dr. John C. Hart
`Curriculum Vitae for Dr. John C. Hart
`Prosecution File History of U.S. Patent No. 8,805,001
`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”)
`U.S. Patent 5,521,843 (“Hashima”)
`U.S. Patent 5,150,432 (“Ueno”)
`D. Trier, A. K. Jain and T. Taxt, “Feature Extraction Methods
`for Character Recognition-A Survey”, Pattern Recognition, vol.
`29, no. 4, 1996, pp. 641–662
`M. H. Glauberman, “Character recognition for business
`machines,” Electronics, vol. 29, pp. 132-136, Feb. 1956
`Declaration of Gerard P. Grenier (authenticating Ex. 1005)
`
`1001
`1002
`1003
`1004
`1005
`
`1006
`1007
`1008
`
`1009
`
`1010
`
`
`
` 1
`
` Citations to non-patent publications are to the original page numbers of the
`
`publication, and citations to U.S. patents are to column:line number of the patents.
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`iv
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`

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`Petition for Inter Partes Review
`Patent No. 8,805,001
`
`I.
`
`INTRODUCTION
`
`Samsung Electronics Co., Ltd. and Samsung Electronics America, Inc.
`
`(collectively, “Petitioner”) request inter partes review (“IPR”) of Claims 1-4 of
`
`U.S. Patent No. 8,805,001 (“the ’001 Patent”) (Ex. 1001), which, on its face, is
`
`assigned to Image Processing Technologies, LLC (“Patent Owner”). This Petition
`
`presents several non-cumulative grounds of invalidity that the U.S. Patent and
`
`Trademark Office (“PTO”) did not consider during prosecution. These grounds
`
`are each likely to prevail, and this Petition, accordingly, should be granted on all
`
`grounds and the challenged claims should be cancelled.
`
`
`
`II. MANDATORY NOTICES UNDER 37 C.F.R. § 42.8
`Real Parties-in-Interest: Petitioner identifies the following real parties-in-
`
`interest: Samsung Electronics Co., Ltd.; Samsung Electronics America, Inc.
`
`Related Matters: Patent Owner has asserted the ’001 Patent against
`
`Petitioner in Image Processing Technologies LLC v. Samsung Elecs. Co., No.
`
`2:16-cv-00505-JRG (E.D. Tex.). Patent Owner has also asserted U.S. Patent Nos.
`
`6,959,293; 7,650,015; 8,983,134; and 8,989,445 in the related action. Petitioner is
`
`concurrently filing IPR petitions for all of these asserted patents.
`
`Lead and Back-Up Counsel:
`
`• Lead Counsel: John Kappos (Reg. No. 37,861), O'Melveny & Myers
`
`LLP, 610 Newport Center Drive, 17th Floor, Newport Beach,
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`1
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`

`
`Petition for Inter Partes Review
`Patent No. 8,805,001
`California 92660. (Telephone: 949-823-6900; Fax: 949-823-6994;
`
`Email: jkappos@omm.com.)
`
`• Backup Counsel: Nick Whilt (Reg. No. 72,081), Brian M. Cook (Reg.
`
`No. 59,356), O'Melveny & Myers LLP, 400 S. Hope Street, Los
`
`Angeles, CA 90071. (Telephone: 213-430-6000; Fax: 213-430-6407;
`
`Email: nwhilt@omm.com, bcook@omm.com.)
`
`Service Information: Samsung consents to electronic service by email to
`
`IPTSAMSUNGOMM@OMM.COM. Please address all postal and hand-delivery
`
`correspondence to lead counsel at O’Melveny & Myers LLP, 610 Newport Center
`
`Drive, 17th Floor, Newport Beach, California 92660, with courtesy copies to the
`
`email address identified above.
`
`III. PAYMENT OF FEES UNDER 37 C.F.R. § 42.15(a)
`The Office is authorized to charge an amount in the sum of $23,000 to
`
`Deposit Account No. 50-0639 for the fee set forth in 37 CFR § 42.15(a), and any
`
`additional fees that might be due in connection with this Petition.
`
`IV. GROUNDS FOR STANDING
`Petitioner certifies that the ’001 Patent is available for IPR and Petitioner is
`
`not barred or estopped from requesting IPR on the grounds identified herein.
`
`V.
`
`PRECISE RELIEF REQUESTED
`
`Petitioner respectfully requests review of Claims 1-4 of the ’001 Patent, and
`
`2
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`

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`Petition for Inter Partes Review
`Patent No. 8,805,001
`cancellation of these claims, based on the grounds listed below:
`
`• Ground 1: Claims 1-4 are obvious under 35 U.S.C. § 103(a) over
`
`Gilbert in view of Hashima;
`
`• Ground 2: Claims 1-4 are obvious under 35 U.S.C. § 103(a) over
`
`Hashima in view of Ueno; and
`
`• Ground 3: Claims 1-4 are obvious under 35 U.S.C. § 103(a) over
`
`Ueno in view of Gilbert.
`
`VI. LEGAL STANDARDS
`A. Claim Construction
`For expired claims, the Federal Circuit has held that the claims should be
`
`construed according to the Phillips v. AWH Corp. standard applicable in district
`
`court. See In re Rambus Inc. 753 F.3d 1253, 1256 (Fed. Cir. 2014). Under
`
`Philips, terms are given “the meaning that [a] term would have to a person of
`
`ordinary skill in the art in question at the time of the invention.” Phillips v. AWH
`
`Corp., 415 F.3d 1303, 1316 (Fed. Cir. 2005). Under 37 C.F.R. 42.100(b), the
`
`PTAB may also apply a district court-type claim construction if the patent is to
`
`expire within 18 months of the entry of the Notice of Filing Date.
`
`The ’001 Patent will expire on December 2, 2017—within 18 months of the
`
`Notice of Filing Date. Thus, for purposes of this proceeding, Petitioner has applied
`
`the Phillips standard to all claim construction issues. See also Ex. 1002, ¶49.
`
`3
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`Petition for Inter Partes Review
`Patent No. 8,805,001
`
`Level Of Ordinary Skill In The Art
`
`B.
`One of ordinary skill in the art the time of the alleged invention of the ’001
`
`Patent would have had either (1) a Master’s Degree in Electrical Engineering or
`
`Computer Science or the equivalent plus at least a year of experience in the field of
`
`image processing, image recognition, machine vision, or a related field or (2) a
`
`Bachelor’s Degree in Electrical Engineering or Computer Science or the equivalent
`
`plus at least three years of experience in the field of image processing, image
`
`recognition, machine vision, or a related field. Additional education could
`
`substitute for work experience and vice versa. Ex. 1002, ¶¶44-48.
`
`VII. OVERVIEW OF THE RELEVANT TECHNOLOGY AND ’001
`PATENT
`
`The purported invention of the ’001 Patent relates to identifying and tracking
`
`a target in an input signal using one or more histograms derived from an image
`
`frame in the video signal. See e.g., Ex. 1001, Claims 1-4; Ex. 1002, ¶¶31-33.
`
`Video image processing and the use of histograms to identify and track targets, and
`
`to derive other information from a video signal were well known at the time the
`
`asserted patents were filed. Ex. 1002, ¶¶23-30, 60, 70, 77. An input signal used in
`
`the purported invention has “a succession of frames, each frame having a
`
`succession of pixels.” Ex. 1001, 3:28-31. The input signal may be a video signal
`
`or any other signal that “generates an output in the form of an array of information
`
`corresponding to information observed by the imaging device,” such as
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`Petition for Inter Partes Review
`Patent No. 8,805,001
`“ultrasound, IR, Radar, tactile array, etc.” Ex. 1001, 9:26-29; Ex. 1002, ¶32. The
`
`’001 Patent then constructs a histogram showing the frequency of pixels meeting a
`
`certain characteristic. The characteristics used to form histograms are referred to
`
`as “domains” in the ’001 Patent. Ex. 1002, ¶34. The ’001 Patent teaches that “the
`
`domains are preferably selected from the group consisting of i) luminance, ii)
`
`speed (V), iii) oriented direction (DI), iv) time constant (CO), v) hue, vi)
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`saturation, and vii) first axis (x(m)), and viii) second axis (y(m)).” Ex. 1001, 4:2-6;
`
`Ex. 1002, ¶¶34, 36. Figure 11 shows histogram processors that can create
`
`histograms in various domains:
`
`
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`Petition for Inter Partes Review
`Patent No. 8,805,001
`The histograms include a plurality of “classes” within a given domain. Ex.
`
`1002, ¶35. Figure 14a (and its accompanying description) illustrates an example of
`
`“classes” within a domain:
`
`
`
`FIG. 14a shows an example of the successive classes C1
`
`C2…Cn−1 Cn, each representing a particular velocity, for a
`
`hypothetical velocity histogram, with
`
`their being
`
`categorization for up to 16 velocities (15 are shown) in
`
`this example. Also shown is envelope 38, which is a
`
`smoothed representation of the histogram.
`
`Ex. 1001, 20:54-59.
`
`The ’001 Patent then uses the histograms to identify a target in the input
`
`signal. For example, one embodiment of the ’001 Patent performs “automatic
`
`framing of a person…during a video conference.” Id. at 22:10-12, Figure 15:
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`Petition for Inter Partes Review
`Patent No. 8,805,001
`
`The system constructs histograms in the X- and Y-domains counting the
`
`number of pixels where the differences in luminance between successive frames
`
`are above certain threshold values:
`
`
`
`The pixels with greatest movement within the image will
`
`normally occur at the peripheral edges of the head of the
`
`subject, where even due to slight movements, the pixels
`
`will vary between the luminance of the head of the
`
`subject and the luminance of the background. Thus, if
`
`the system of the invention is set to identify only pixels
`
`with DP=1, and to form a histogram of these pixels, the
`
`histogram will detect movement peaks along the edges of
`
`the face where variations in brightness, and therefore in
`
`pixel value, are the greatest, both in the horizontal
`
`projection along Ox and in the vertical projection along
`
`7
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`Petition for Inter Partes Review
`Patent No. 8,805,001
`
`Oy.
`
`Id. at 22:49-59, 10:30-58 (explaining that DP is set to “1” when pixel value of the
`
`pixel under consideration has “undergone significant variation as compared
`
`to…the same pixel in the prior frame”); Ex. 1002, ¶¶36-37. Figures 16 and 17
`
`show camera setup and the histogram constructed using this method:
`
`Ex. 1001, Fig. 16
`
`
`
`Ex. 1001, Fig. 17
`
`In addition, the system may also be used to automatically track a target by “a
`
`
`
`spotlight or a camera. Using a spotlight the invention might be used on a
`
`helicopter to track a moving target on the ground, or to track a performer on a stage
`
`during an exhibition. The invention would similarly be applicable to weapons
`
`targeting systems.” Ex. 1001, 23:40-46; Ex. 1002, ¶¶38-39. In such applications,
`
`the system uses X- and Y-minima and maxima of the histograms in X- and Y-
`
`domains to determine the center of the target:
`
`8
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`Petition for Inter Partes Review
`Patent No. 8,805,001
`In a preferred embodiment, the new center of the area is
`
`determined to be (XMIN+XMAX)/2, (YMIN+YMAX)/2, where
`
`XMIN and XMAX are the positions of the minima and
`
`maxima of the x projection histogram, and YMIN and
`
`YMAX are the positions of the minima and maxima of the
`
`y projection histogram.
`
`Ex. 1001, 24:50-55. The patent defines “the positions of the minima” of a
`
`projection histogram to be the smallest X- (and Y) coordinate of any pixel in the
`
`image region whose validation signal is “1.” Ex. 1002, ¶¶40-41. Similarly the
`
`maximum is the largest X- (and Y) coordinate of any pixel in the image region
`
`whose validation signal is “1.” Id. The system may recalculate the histograms at
`
`regular intervals and use those points to again find the center coordinates as the
`
`new frames are received. Ex. 1002, ¶42.
`
`Once the center of the target is determined, the center is used to adjust the
`
`camera or spotlight to be directed to the moving target:
`
`Having acquired the target, controller 206 controls
`
`servomotors 208 to maintain the center of the target in
`
`the center of the image….
`
`It will be appreciated that as the target moves, the
`
`targeting box will move with the target, constantly
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`Petition for Inter Partes Review
`Patent No. 8,805,001
`adjusting the center of the targeting box based upon the
`
`movement of the target, and enlarging and reducing the
`
`size of the targeting box. The targeting box may be
`
`displayed on monitor 212, or on another monitor as
`
`desired to visually track the target.
`
`Ex. 1001, 25:12-25; Ex. 1002, ¶43. Figure 23 shows an example of the targeting
`
`box in a frame:
`
`Ex. 1001, Fig. 23
`
`
`
`VIII. DETAILED EXPLANATION OF GROUNDS
`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)
`
`The purported invention of the ’001 Patent relates to a process of identifying
`
`a target in digitized visual input by using histograms of pixel characteristics and
`
`10
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`Petition for Inter Partes Review
`Patent No. 8,805,001
`tracking the target. However, researchers at U.S. Army White Sands Missile
`
`Range, New Mexico, in collaboration with New Mexico State University, Las
`
`Cruces, had already developed a system that utilizes histograms to identify and
`
`track targets, and they published their findings in January 1980, more than 17 years
`
`before the earliest effective filing date of the ’001 Patent. Ex. 1002, ¶50; Ex. 1010,
`
`Grenier Decl.
`
`The article, entitled “A Real-Time Video Tracking System,” published in
`
`IEEE Transactions on Pattern Analysis and Machine Intelligence in January 1980
`
`(“Gilbert”), qualifies as prior art under pre-AIA § 102(b). Gilbert describes “a
`
`system for missile and aircraft identification and tracking…applied in real time to
`
`identify and track objects.” Ex. 1002, ¶51; Ex. 1005, 47. Gilbert was not of record
`
`and was not considered during prosecution of the ’001 Patent. The Gilbert system
`
`includes an image processing system comprising a video processor, a projection
`
`processor, a tracker processor, and a control processor as shown in Figure 1,
`
`reproduced below. Ex. 1002, ¶51; Ex. 1005, 48.
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`Petition for Inter Partes Review
`Patent No. 8,805,001
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`
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`The video processor receives a digitized video signal comprising 60 fields/s,
`
`i.e., 30 frames/s, as input. Ex. 1002, ¶52; Ex. 1005, 48. Each field—i.e., frame—
`
`consists of a succession of n X m pixels:
`
`As the TV camera scans the scene, the video signal is
`
`digitized at m equally spaced points across each
`
`horizontal scan. During each video field, there are n
`
`horizontal scans which generate an n X m discrete matrix
`
`representation at 60 fields/s.
`
`Ex. 1005, 48. Although Gilbert uses the word “field” instead of “frame,” a POSA
`
`would have understood that a “frame” consists of two “fields” in the context in
`
`which they are used in Gilbert. (At the time, video signals were interlaced such
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`Petition for Inter Partes Review
`Patent No. 8,805,001
`that a frame of a non-interlaced video consisted of two fields. The first field would
`
`be the odd numbered scanlines and the second field would be the even numbered
`
`scanlines recorded 1/60th of a second later than the first field.) Ex. 1002, ¶52.
`
`Gilbert then constructs histograms of pixels in the 256 gray-level classes in the
`
`intensity domain:
`
`Every 96 ns, a pixel intensity is digitized and quantized
`
`into eight bits (256 gray levels), counted into one of six
`
`256-level histogram memories, and then converted by a
`
`decision memory
`
`to a 2-bit code
`
`indicating
`
`its
`
`classification (target, plume, or background.).
`
`Ex. 1005, 48, 49 (“Then the entire region has been scanned, h contains the
`
`distribution of pixels over intensity and is referred to as the feature histogram of
`
`the region R.”). In other words, the Video Processor of Gilbert creates histograms
`
`using the intensity domain over classes of all intensity values. Ex. 1002, ¶52.
`
`Although Gilbert uses histograms in the intensity domain as examples, it also notes
`
`that other “features that can be functionally derived from relationship between
`
`pixels, e.g., texture, edge, and linearity measure” may be used. Ex. 1005, 48; Ex.
`
`1002, ¶53.
`
`Using the histograms, the video processor “separates the target from the
`
`background,” i.e., identifies the target. Ex. 1005, 48. Gilbert uses probability
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`Petition for Inter Partes Review
`Patent No. 8,805,001
`estimates based on a 256 level grayscale histogram to determine whether a
`
`particular pixel belongs to the target, plume, or background region. Ex. 1002, ¶52.
`
`This identification is repeated for each frame. See Ex. 1005, 47 (“The camera
`
`output is statistically decomposed into background, foreground, target, and plume
`
`region by the video processor, with this operation carried on at video rate for up to
`
`the full frame.”).
`
`Once the video processor identifies the pixels belonging to the target, the
`
`video processor creates “a binary picture, where target presence is represented by a
`
`‘1’ and target absence by a ‘0.’” Ex. 1005, 50 (“In the projection processor, these
`
`matrices are analyzed field-by-field at 60 field/s using projection based
`
`classification algorithm to extract the structural and activity parameters needed to
`
`identify and track the target.”); Ex. 1002, ¶54. This binary picture indicates to the
`
`projection processor whether or not a pixel should be considered further in
`
`constructing X- and Y-projections. Ex. 1002, ¶54. A projection processor creates
`
`projections using only the pixels identified for inclusion. Ex. 1002, ¶55. Although
`
`these projections are not explicitly referred to by Gilbert as projection histograms,
`
`reference to Figure 4 of Gilbert (annotated below) clearly shows four different
`
`projection histograms formed using the target pixels:
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`14
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`Petition for Inter Partes Review
`Patent No. 8,805,001
`
`
`
`In addition, Gilbert explains that a projection “gives the number of object points
`
`along parallel lines; hence it is a distribution of the target points for a given view
`
`angle.” Ex. 1005, 50. Thus, these Figure 4 projections will be referred to as
`
`projection histograms throughout this petition.
`
`The projection processor then identifies the target location, orientation, and
`
`structure using the projection histograms:
`
`The
`
`target
`
`location, orientation, and structure are
`
`characterized by the pattern of 1 entries in the binary
`
`picture matrix, and the target activity is characterized by
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`Petition for Inter Partes Review
`Patent No. 8,805,001
`a sequence of picture matrices. In the projection
`
`processor, these matrices are analyzed field-by-field at 60
`
`fields/s [i.e., 30 frames/s]….
`
`Ex. 1005, 50. The projection processor computes a center of area point for the
`
`target in order to “precisely determine the target position and orientation.” Id.; Ex.
`
`1002, ¶56. This calculation is done by first finding a center of area for each of top
`
`and bottom portions using the projection histograms in X- and Y-domains for the
`
`top and bottom portions of the target. Ex. 1002, ¶¶56-57. The projection
`
`processor then uses these center-of-area points to determine a target center-of-area
`
`point. This is shown in Figure 4, reproduced below (with annotations):
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`16
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`Petition for Inter Partes Review
`Patent No. 8,805,001
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`
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`The tracker processor analyzes information, such as the target’s size,
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`location, and orientation, from the projection processor and outputs information
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`such as “1) tracking window size, 2) tracking window shape, and 3) tracking
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`window position.” Ex. 1005, 52; Ex. 1002, ¶59. The video processor then uses
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`this information to draw a tracking window, i.e., a tracking box, around the target.
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`See id. The display of the tracking box in the frame is shown in Figure 2.
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`The tracker processor also outputs the target’s movements to the control
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`processor, which controls the direction and zoom scale of the lens to follow the
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`target:
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`The outputs to the control processor are used to control
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`the target location and size for the next frame. The bore-
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`sight correction signals are used to control the azimuth
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`and elevation pointing angles of the telescope. The
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`desired zoom is used to control the zoom lens, keeping
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`the target visible within the FOV. The desired image
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`rotation controls the image rotation element to keep the
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`target image vertical.
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`Ex. 1005, 52.
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`The histogram formation and target identification process of Gilbert is
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`performed on a frame-by-frame basis. Ex. 1005, 52; Ex. 1002, ¶58.
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`Patent No. 8,805,001
`U.S. Patent No. 5,521,843 (“Hashima”) (Ex. 1006)
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`2.
`Hashima also discloses a “system for and method of recognizing and
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`tracking a target mark…by processing an image of the target mark produced by a
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`video camera.” Ex. 1006, 1:6-12. Hashima qualifies as prior art under pre-AIA 35
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`U.S.C. §§ 102(a), 102(b), 102(e), and § 119 (“but no patent shall be granted…for
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`an invention which had been…described in a printed publication in any country
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`more than one year before the date of the actual filing of the application in this
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`country.”). Although Hashima was of record, it was not applied during
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`prosecution of the ’001 Patent. Hashima uses an image processing system that
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`takes input from a video camera and identifies the target shape based on
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`histograms constructed from pixel characteristics. Ex. 1002, ¶¶61-62. Once the
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`target shape is detected, Hashima uses the histogram information to determine the
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`location of the target, and move a robot arm based on the information to grip the
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`target object. One embodiment of this system is shown in Figure 1, reproduced
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`below.
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`Patent No. 8,805,001
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`Hashima uses a pre-determined mark, a black circle with white triangle
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`inside, as shown in Figure 3 below, and Hashima notes that “target marks of
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`various configurations…can be detected by the [disclosed] process.” Ex. 1006,
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`10:20-23; Ex. 1002, ¶62. The histograms of the exemplary mark in X- and Y-
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`domains counting the number of black pixels are shown in Figure 6.
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`Hashima Fig. 3
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`
`
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`The image processor reads input from the video camera, converts the image
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`Hashima Fig. 6
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`
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`into a binary image, and constructs a histogram of the binary images. Ex. 1006,
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`8:22-30 (“X- and Y-projected histograms of the target mark image are determined
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`…. The X-projected histogram represents the sum of pixels having the same X-
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`coordinates, and the Y-projected histogram represents the sum of pixels having the
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`same Y-coordinates.”); Ex. 1002, ¶62. See generally, Ex. 1006, 8:18-9:7. Then
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`the image processor determines whether the image represents the target by
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`counting the number of peaks and valleys in the projected histogram. Ex. 1006,
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`9:8-9:13; Ex. 1002, ¶63. If the number matches the number of peaks and valleys
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`of the X- and Y-projected histograms as shown in Figure 6 (reproduced above), the
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`system identifies the image as that of the target mark. Id. at 9:13-9:23; Ex. 1002,
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`¶63. Figure 5 shows the flow chart describing the detection process:
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`Once the target mark is detected, Hashima determines the center of the
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`detected mark from the X- and Y-maxima and minima of the X- and Y-histograms:
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`
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`The image processor 40…generat[es] a histogram 15
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`projected onto the X-axis and a histogram 16 projected
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`onto the Y-axis, and then determines the X and Y
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`coordinates of the central position Pm (mx, my) from the
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`projected histograms 15, 16.
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` Specifically, the X
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`Patent No. 8,805,001
`coordinate mx of the central position Pm (mx, my) can be
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`determined using opposite end positions Xb1, Xb2
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`obtained from the X-projected histogram 15 according to
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`the following equation (3):
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`mx=(Xb1+Xb2)/2
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`
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`
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`
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`(3).
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`The Y coordinate my of the central position Pm (mx, my)
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`can be determined using opposite end positions Yb1, Yb2
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`obtained from the Y-projected histogram 16 according to
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`the following equation (4):
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`my=(Yb1+Yb2)/2
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`
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`(4).
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`Id. at 11:6-25; Ex. 1002, ¶¶65-66. Figure 15 illustrates the process for finding the
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`center position of the detected target:
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`The center of the target is then compared to the center of the image memory
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`from the previous frame to find the shift of the target in the X- and Y-directions.
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`The shift amount is used to move the robot arm (and the camera mounted thereon)
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`Patent No. 8,805,001
`toward the target, and is recalculated based on new images as the robot arm and the
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`camera move toward the target, until the object is gripped. Ex. 1002, ¶¶64, 67; Ex.
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`1006, 14:61-15:37. Figure 27 shows a flow chart describing the process:
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`
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`Patent No. 8,805,001
`As the target is tracked, Hashima displays a rectangular window around the
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`target—i.e., a tracking box. Ex. 1006, 14:29-34, Figure 23. As the system
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`receives new frames from the video camera, the target and window locations are
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`recalculated using the new histograms created from each new frame:
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`When the target mark 10 starts to be tracked, the window
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`is established using the projected histogram information
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`obtained when the target mark image is recognized.
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`When the target mark 10 is subsequently tracked, the
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`window
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`[44]
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`is established using new projected
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`histogram information obtained upon each measurement
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`made by the camera 20.
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`Id. at 14:29-34; Ex. 1002, ¶68. Figure 23 shows the target window 44 around the
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`target mark 10A.
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`Hashima Fig. 23
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`
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`Patent No. 8,805,001
`A block diagram of the system in Hashima shows that after determining an
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`appropriate window, the image is displayed on a monitor, 315. See also, Ex. 1007,
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`Hashima at 25:34–38, Figure 52; Ex. 1002, ¶69.
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`
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`U.S. Patent No. 5,150,432 (“Ueno”) (Ex. 1007)
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`3.
`A similar process and apparatus is described in Ueno. Ueno uses histograms
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`in X- and Y-domains to identify the facial region in the frames of video signals,
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`and tracks the facial region with a rectangle constructed from X- and Y-minima
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`and maxima derived from the histograms. Ex. 1007, 1:39-68; Ex. 1002, ¶71. Ueno
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`qualifies as prior art under pre-AIA § 102(b). Ueno was not of record and was not
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`considered during prosecution of the ’001 Patent.
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`Ueno describes a video encoding system that includes “frame memory 101
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`for storing image signals for one frame” connected to “a facial region detecting
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`circuit 102 for detecting human facial region of the frame data….” Ex. 1007, 3:5-
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`7; Ex. 1002, ¶72. In Ueno, “video signals are sequentially input to the image input
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`terminal 100 in frames.” Ex. 1007, 4:25-26. “The image signal is written in the
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`frame memory 101 as frame data one frame by one frame. The frame data written
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`in the frame memory 101…is supplied to the facial region detecting circuit 102….”
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`Ex. 1007, 4:33-37. The facial region detecting circuit of Ueno uses differences
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`between two consecutive