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
`
`____________________
`
`Case No. IPR2017-01190
`U.S. Patent No. 6,717,518
`____________________
`
`PETITIONER’S DEMONSTRATIVES FOR ORAL HEARING
`(EXHIBIT 1020)
`
`SAMSUNG EXHIBIT 1020
`Samsung v. Image Processing Techs.
`
`
`
`____________________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`____________________
`
`SAMSUNG ELECTRONICS CO., LTD. AND
`SAMSUNG ELECTRONICS AMERICA, INC.
`Petitioner
`
`v.
`
`IMAGE PROCESSING TECHNOLOGIES LLC,
`Patent Owner
`
`____________________
`
`Case No. IPR2017-01190
`U.S. Patent No. 6,717,518
`____________________
`
`PETITIONER’S DEMONSTRATIVES FOR ORAL HEARING
`(EXHIBIT 1020)
`
`SAMSUNG EXHIBIT 1020
`Samsung v. Image Processing Techs.
`
`
`
`UNITED STATES PATENT AND TRADEMARK OFFICE
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`U.S. Patent No. 6,717,518
`
`Samsung Electronics Co., Ltd. and
`Samsung Electronics America, Inc.,
`Petitioners,
`
`v.
`Image Processing Technologies, LLC,
`Patent Owner.
`
`CASE IPR2017-01190
`
`Oral Argument
`Samsung’s Demonstrative Exhibits
`June 29, 2018
`
`1
`
`SAMSUNG EX. 1020
`
`
`
`Overview of the ’518 Patent
`
`Claim Construction
`
`Instituted Grounds for Review
`Eriksson + Stringa
`Ando + Suenaga
`Ando + Stringa
`
`2
`
`SAMSUNG EX. 1020
`
`
`
`Overview of the ’518 Patent
`
`Claim Construction
`
`Instituted Grounds for Review
`Eriksson + Stringa
`Ando + Suenaga
`Ando + Stringa
`
`3
`
`SAMSUNG EX. 1020
`
`
`
`The ’518 Patent
`
`’518 Patent (Ex. 1001) at Cover.
`
`4
`
`SAMSUNG EX. 1020
`
`
`
`’518 Patent, Claim 39
`
`[pre]
`
`[a]
`
`[b]
`
`[c]
`
`[d]
`
`[e]
`
`[f]
`
`[g]
`
`’518 Patent (Ex. 1001) at Claim 39.
`
`5
`
`SAMSUNG EX. 1020
`
`
`
`Example of Claimed Invention
`
`39[a]
`
`“acquiring an image of the face of the person, the image comprising pixels
`corresponding to the feature to be detected”
`
`39[b]
`
`“identifying a characteristic of the face other than the feature to be detected”
`
`39[c]
`
`“identifying a portion of the image of the face comprising the feature to be
`detected using an anthropomorphic model based on the location of the
`identified facial characteristic”
`
`• Face image is acquired
`
`• Identify nostrils (272) or “any other facial
`characteristic”
`
`• Position of nostrils is used to identify a portion of the
`image where pupil is likely located (276)
`
`’518 Patent (Ex. 1001) at Fig. 32.
`
`’518 Patent (Ex. 1001) at Fig. 32; PO Response (Paper 15) at 23–24; Petition (Paper 2) at 8.
`
`6
`
`SAMSUNG EX. 1020
`
`
`
`Example of Claimed Invention
`
`39[d]
`
`“selecting pixels of the portion of the image having characteristics
`corresponding to the feature to be detected”
`
`39[e]
`
`“forming at least one histogram of the selected pixels”
`
`• Pixels are selected because they have
`characteristics of the pupil
`(e.g., “low luminance and high gloss”)
`
`• Vertical and horizontal histograms are formed
`of those pixels
`
`• As indicated by the red arrows, more than just
`pupil pixels are included in the histograms
`
`’518 Patent (Ex. 1001) at 30:61–31:2, Fig. 36; Reply (Paper 19) at 8; Petition (Paper 2) at 10.
`
`7
`
`SAMSUNG EX. 1020
`
`
`
`Example of Claimed Invention
`
`39[f]
`
`“analyzing the at least one histogram over time to identify characteristics of
`the feature to be detected”
`
`39[g]
`
`“said feature being the iris, pupil or cornea”
`
`’518 Patent (Ex. 1001) at Fig. 33.
`’518 Patent (Ex. 1001) at Fig. 34.
`Histograms are analyzed over time to identify whether the pupil
`is present or absent, i.e., a blink.
`’518 Patent (Ex. 1001) at 31:24–67, Figs. 33, 34; Petition (Paper 2) at 9; PO Response (Paper 15) at 25–27.
`
`8
`
`SAMSUNG EX. 1020
`
`
`
`Overview of the ’518 Patent
`
`Claim Construction
`
`Instituted Grounds for Review
`Eriksson + Stringa
`Ando + Suenaga
`Ando + Stringa
`
`9
`
`SAMSUNG EX. 1020
`
`
`
`Patent Owner Construes Several Terms
`
`Element
`
`Construed Term
`
`[e], [f]
`
`“histogram”
`
`[c]
`
`“anthropomorphic model”
`
`[b], [c]
`
`“characteristic of the face” / “facial characteristic”
`
`[d], [e]
`
`“selecting pixels of the portion of the image having
`characteristics corresponding to the feature to be
`detected” / “forming at least one histogram of the
`selected pixels”
`
`’518 Patent (Ex. 1001) at Claim 39.
`
`10
`
`SAMSUNG EX. 1020
`
`
`
`PO’s Construction: 39[e], [f]: “Histogram”
`
`Element
`
`Construed Term
`
`[e], [f]
`
`“histogram”
`
`[c]
`
`“anthropomorphic model”
`
`[b], [c]
`
`“characteristic of the face” / “facial characteristic”
`
`[d], [e]
`
`“selecting pixels of the portion of the image having
`characteristics corresponding to the feature to be
`detected” / “forming at least one histogram of the
`selected pixels”
`
`Ex. 1001 at Claim 39.
`
`11
`
`SAMSUNG EX. 1020
`
`
`
`PO’s Construction: 39[e], [f]: “Histogram”
`
`Construction Unnecessary
`• Ground A: Eriksson expressly discloses “histogram”
`
`• Grounds B and C: PO does not dispute Ando discloses histogram
`
`Eriksson (Ex. 1005) at 318; Reply (Paper 19) at 2; Petition (Paper 2) at 37.
`
`12
`
`SAMSUNG EX. 1020
`
`
`
`PO’s Construction: 39[c]: “anthropomorphic model”
`
`Element
`
`Construed Term
`
`[e], [f]
`
`“histogram”
`
`[c]
`
`“anthropomorphic model”
`
`[b], [c]
`
`“characteristic of the face” / “facial characteristic”
`
`[d], [e]
`
`“selecting pixels of the portion of the image having
`characteristics corresponding to the feature to be
`detected” / “forming at least one histogram of the
`selected pixels”
`
`Ex. 1001 at Claim 39.
`
`13
`
`SAMSUNG EX. 1020
`
`
`
`PO’s Construction: 39[c]: “anthropomorphic model”
`
`Construction Unnecessary
`
`PO does not contest disclosure for any of the grounds
`
`Reply (Paper 19) at 3.
`
`14
`
`SAMSUNG EX. 1020
`
`
`
`PO’s Construction: 39[b], [c]:
`“facial characteristic” / “characteristics of the face”
`
`Element
`
`Construed Term
`
`[e], [f]
`
`“histogram”
`
`[c]
`
`“anthropomorphic model”
`
`[b], [c]
`
`“characteristic of the face” / “facial characteristic”
`
`[d], [e]
`
`“selecting pixels of the portion of the image having
`characteristics corresponding to the feature to be
`detected” / “forming at least one histogram of the
`selected pixels”
`
`’518 Patent (Ex. 1001) at Claim 39.
`
`15
`
`SAMSUNG EX. 1020
`
`
`
`PO’s Construction: 39[b], [c]:
`“facial characteristic” / “characteristics of the face”
`
`Construction Unnecessary
`
`• Grounds A and C: PO does not contest disclosure
`
`• Ground B: PO does not contest Ando discloses this
`limitation (only argues Suenaga does not)
`
`• Institution Decision: PO’s arguments “do not apply
`because we rely upon Ando . . . .”
`
`• Suenaga: Disclosed even under PO’s construction
`
`Reply (Paper 19) at 3–5, 27–28; Inst. Dec. (Paper 11) at 24.
`
`16
`
`SAMSUNG EX. 1020
`
`
`
`PO’s Construction: 39[b], [c]:
`“facial characteristic” / “characteristics of the face”
`
`PO’s Proposed Construction: “distinguishing element of a face,
`such as the nose, nostril, ears, eyebrows, mouth, etc.”
`
`Inconsistent with the specification
`
`“While the invention is being described with respect to identification
`of the nostrils as a starting point to locating the eyes, it is foreseen that
`any other facial characteristic, e.g., the nose, ears, eyebrows, mouth,
`etc., and combinations thereof, may be detected as a starting point
`for locating the eyes. These characteristics may be discerned from any
`characteristics capable of being searched by the system, including
`CO, DP, velocity, direction, luminance, hue and saturation.”
`
`’518 Patent at 29:52–60.
`
`Reply (Paper 19) at 3–5; PO Response (Paper 15) at 32–34.
`
`17
`
`SAMSUNG EX. 1020
`
`
`
`PO’s Incorrect Interpretation: 39[d], [e]: “selecting pixels”
`
`Element
`
`Construed Term
`
`[e], [f]
`
`“histogram”
`
`[c]
`
`“anthropomorphic model”
`
`[b], [c]
`
`“characteristic of the face” / “facial characteristic”
`
`[d], [e]
`
`“selecting pixels of the portion of the image having
`characteristics corresponding to the feature to be
`detected” / “forming at least one histogram of the
`selected pixels”
`
`’518 Patent (Ex. 1001) at Claim 39.
`
`18
`
`SAMSUNG EX. 1020
`
`
`
`PO’s Incorrect Interpretation: 39[d], [e]: “selecting pixels”
`
`39[d], [e]
`
`“selecting pixels of the portion of the image having
`characteristics corresponding to the feature to be detected” /
`“forming at least one histogram of the selected pixels”
`
`PO advances no construction, but argues these limitations require:
`• selecting “only iris, pupil, or cornea pixels”
`• “not merely selecting all the pixels in a particular area”
`
`Inst. Dec.: “We do not agree that the claim limitation … precludes
`selection of pixels that are not of the feature itself.… [C]laim limitation [d]
`… requires selection including pixels having characteristics corresponding
`to the feature, but it does not, however, limit selection to only those pixels
`and others could be included in the selection.”
`
`Inst. Dec. (Paper 11) at 16; PO Response (Paper 15) at 34, 57.
`
`19
`
`SAMSUNG EX. 1020
`
`
`
`PO’s Incorrect Interpretation: 39[d], [e]: “selecting pixels”
`
`39[d], [e]
`
`“selecting pixels of the portion of the image having
`characteristics corresponding to the feature to be detected” /
`“forming at least one histogram of the selected pixels”
`
`The specification does not limit the selection to only pixels of the feature
`being detected, such as a pupil.
`
`’518 Patent
`
`’518 Patent
`
`’518 Patent (Ex. 1001) at Figs. 36, 37; Reply (Paper 19) at 5–12.
`
`20
`
`SAMSUNG EX. 1020
`
`
`
`PO’s Incorrect Interpretation: 39[d], [e]: “selecting pixels”
`
`39[d], [e]
`
`“selecting pixels of the portion of the image having
`characteristics corresponding to the feature to be detected” /
`“forming at least one histogram of the selected pixels”
`
`PO improperly rewrites the claim to include the
`word “only”
`
`“selecting [only those] pixels of the portion of the image having
`characteristics corresponding to the feature to be detected” /
`“forming at least one histogram of [only] the selected pixels”
`
`Reply (Paper 19) at 6–7.
`
`21
`
`SAMSUNG EX. 1020
`
`
`
`PO’s Incorrect Interpretation: 39[d], [e]: “selecting pixels”
`
`39[d], [e]
`
`“selecting pixels of the portion of the image having
`characteristics corresponding to the feature to be detected” /
`“forming at least one histogram of the selected pixels”
`
`“The word ‘comprising’ transitioning from the preamble to
`the body signals that the entire claim is presumptively
`open-ended.”
`Gillette Co. v. Energizer holdings, Inc., 405 F.3d 1367, 1371 (Fed. Cir. 2005)
`(emphases added).
`
`Regardless, the prior art histograms are formed only of pixels that are
`selected and have characteristics corresponding to the pupil.
`
`Reply (Paper 19) at 6–7.
`
`22
`
`SAMSUNG EX. 1020
`
`
`
`PO’s Incorrect Interpretation: 39[d], [e]: “selecting pixels”
`
`39[d], [e]
`
`“selecting pixels of the portion of the image having
`characteristics corresponding to the feature to be detected” /
`“forming at least one histogram of the selected pixels”
`
`PO’s arguments contradict
`its infringement theory in
`District Court
`• PO identified eye region
`(enclosed in red box) as the
`“portion” for 39[c]
`
`• PO included the entire “portion”
`in the histogram for 39[d], [e]
`
`• Histogram includes more than
`just iris, pupil, or cornea pixels
`
`Reply (Paper 19) at 10–12; Infr. Cont. (Ex. 1012) at 56–62.
`
`23
`
`SAMSUNG EX. 1020
`
`
`
`Overview of the ’518 Patent
`
`Claim Construction
`
`Instituted Grounds for Review
`Eriksson + Stringa
`Eriksson + Stringa
`Ando + Suenaga
`Ando + Stringa
`
`24
`
`SAMSUNG EX. 1020
`
`
`
`Overview of Eriksson
`
`• Presented at IEEE Conference
`on Intelligent Transportation
`Systems in November, 1997
`• Detects driver fatigue by
`using histograms to measure
`blink rates
`
`Eriksson (Ex. 1005) at 2, 5, 9; Petition at 10–14.
`
`25
`
`Eriksson (Ex. 1005) at 318.
`
`SAMSUNG EX. 1020
`
`
`
`Overview of Stringa
`
`• Catalogued at UC Davis Library
`on March 5, 1993
`
`• Discloses facial recognition
`system that identifies pupils
`
`• Extensive disclosure of
`anthropomorphic models and
`the calculation of horizontal and
`vertical histograms
`
`• Eriksson explicitly relies on
`Stringa’s face detection
`algorithm
`
`Stringa (Ex. 1006); Petition (Paper 2) at 15–17, 26–41; Reply (Paper 19) at 13–17.
`
`26
`
`SAMSUNG EX. 1020
`
`
`
`Ground A: Obviousness Over Eriksson and Stringa
`
`PO only disputes Eriksson’s and Stringa’s disclosure of:
`
`1. A “histogram”
`
`2. Forming a histogram “of the selected pixels”
`
`27
`
`SAMSUNG EX. 1020
`
`
`
`’518 Patent, Claim 39, Element [e]: “histogram”
`
`[pre]
`
`[a]
`
`[b]
`
`[c]
`
`[d]
`
`[e]
`
`[f]
`
`[g]
`
`Ex. 1001
`
`28
`
`SAMSUNG EX. 1020
`
`
`
`Eriksson Disclosed a “histogram”
`
`ADMITTED
`
`Eriksson
`“Horizontal histogram across the pupil”
`
`PO Prelim. Resp.: “Eriksson
`discloses forming and analyzing a
`histogram . . . . . Figure 5 of
`Eriksson shows this histogram.”
`
`PO Prelim. Resp. (Paper 6) at 30 (emphases added).
`
`Eriksson (Ex. 1005) at 318 (annotation added).
`
`Petition (Paper 2) at 37–38; Reply (Paper 19) at 12–18.
`
`29
`
`SAMSUNG EX. 1020
`
`
`
`Eriksson Discloses a “histogram”
`
`Eriksson (Ex. 1005) at 318 (annotation added).
`
`Eriksson (Ex. 1005) at 317 (emphasis added).
`
`Petition (Paper 2) at 37–38; Reply (Paper 19) at 12–18.
`
`30
`
`Eriksson (Ex. 1005) at 318 (emphasis added).
`
`SAMSUNG EX. 1020
`
`
`
`Eriksson Discloses a “histogram”
`
`Eriksson’s use of the histogram is the same as Figure 36 in the ’518 Patent
`
`Eriksson
`
`’518 Patent
`
`Eriksson (Ex. 1005) at 318 (annotations added).
`
`Petition (Paper 2) at 37–38; Reply (Paper 19) at 12–18, 23.
`
`31
`
`SAMSUNG EX. 1020
`
`
`
`Eriksson Discloses a “histogram”
`
`Even under PO’s argument that Figure 5 shows “plots of
`the intensity values for pixels on a particular horizontal
`line,” the construction is still satisfied
`
`Dr. Hart: What is counted
`is “the frequency of photons
`or other radiometric energy,
`radiometric power
`specifically.”
`
`Hart Dep. (Ex. 2003) at 143:14–144:23.
`
`Eriksson (Ex. 1005) at 318 (annotation added).
`
`Reply (Paper 19) at 15–16; PO Response (Paper 15) at 47–48.
`
`32
`
`SAMSUNG EX. 1020
`
`
`
`Eriksson Discloses a “histogram”
`
`39[f]
`
`“analyzing the at least one histogram over time to identify
`characteristics of the feature to be detected”
`
`Contrary to PO argument, Eriksson uses its histograms
`
`Eriksson (Ex. 1005) at 317 (emphasis added).
`
`Eriksson (Ex. 1005) at 318.
`
`Reply (Paper 19) at 17–18.
`
`Eriksson (Ex. 1005) at 318 (emphasis added).
`
`33
`
`SAMSUNG EX. 1020
`
`
`
`Eriksson Discloses a “histogram”
`
`39[f]
`
`“analyzing the at least one histogram over time to identify
`characteristics of the feature to be detected”
`
`Contrary to PO argument regarding the “matching function,’
`Eriksson uses its histograms
`
`Horizontal histogram across the pupil
`
`When the eye is open, the valley in
`the intensity-curve [histogram]
`corresponding to the pupil will be
`surrounded by two large peaks
`corresponding to the sclera. When
`the eye is closed, this curve is usually
`very flat in the center…. This will lead
`to a good match when the eye is open,
`and very likely to a bad match when
`the eye is closed.
`
`Eriksson (Ex. 1005) at 318.
`
`Reply (Paper 19) at 18.
`
`Eriksson (Ex. 1005) at 318
`(annotation added).
`
`34
`
`SAMSUNG EX. 1020
`
`
`
`Stringa Discloses a “histogram”
`
`ADMITTED
`
`Stringa
`“… the search of the pupil is based
`on the analysis of the horizontal
`grey-level distribution.”
`
`Stringa (Ex. 1006) at 377 (emphasis added).
`
`PO Prelim. Resp.: “Stringa forms a
`horizontal grey-level histogram …
`Stringa uses the second derivative of
`this histogram to detect an eye pupil
`location…Stringa relies on the shape
`of the second derivative curve of the
`histogram that is based on grey-level
`values of all pixels in the zone to identify
`the pupil location.”
`PO Prelim. Resp. (Paper 6) at 31–32 (emphasis added).
`
`35
`
`Stringa (Ex. 1006) at Fig. 3 (emphases added).
`
`Petition (Paper 2) at 37–38; Reply (Paper 19) at 12–18.
`
`SAMSUNG EX. 1020
`
`
`
`Stringa Discloses a “histogram”
`
`Stringa refers to “histograms” as “distributions”
`
`“The projection of the
`horizontal leading edges
`along the vertical axis defines
`the vertical histogram H(y).”
`
`Stringa (Ex. 1006) at 372 (emphasis added).
`
`H(y)
`
`Stringa (Ex. 1006) at Fig. 3 (emphases added).
`
`Stringa (Ex. 1006) at Fig. 3, 372. Reply (Paper 19) at 13.
`
`36
`
`SAMSUNG EX. 1020
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`
`
`Stringa Discloses a “histogram”
`
`Stringa uses a horizontal grey-level histogram to find the pupil
`
`Stringa (Ex. 1006) at 377 (highlighting added).
`
`PO Prelim. Resp.: “Stringa forms a horizontal grey-level histogram . . . .”
`
`PO Prelim. Resp. (Paper 6) at 31.
`
`Petition (Paper 2) at 37–38; Reply (Paper 19) at 12–18; PO Response (Paper 15) at 51.
`
`37
`
`SAMSUNG EX. 1020
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`
`
`Stringa Discloses a “histogram”
`
`Stringa includes formulas explaining
`how to calculate horizontal and vertical histograms
`
`Step 1: Threshold each pixel (Im/C)
`
`Step 3: Plot sums on axis
`
`Stringa (Ex. 1006) at 371.
`
`Step 2: Sum the pixels
`
`Stringa (Ex. 1006) at 372.
`
`Reply (Paper 19) at 13–18.
`
`Stringa (Ex. 1006) at Fig. 3 (annotation added);
`Reply (Paper 19) at 15.
`
`38
`
`SAMSUNG EX. 1020
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`
`
`’518 Patent, Claim 39[d], [e]
`
`[pre]
`
`[a]
`
`[b]
`
`[c]
`
`[d]
`
`[e]
`
`[f]
`
`[g]
`
`Ex. 1001
`
`39
`
`SAMSUNG EX. 1020
`
`
`
`’518 Patent, Claim 39[d], [e]
`
`39[d], [e]
`
`“selecting pixels of the portion of the image having characteristics corresponding to
`the feature to be detected” / “forming at least one histogram of the selected pixels”
`
`• PO’s argument is based on its interpretation that requires
`selection of only pixels of the feature
`Inst. Dec.: “We do not agree that the claim limitation … precludes
`selection of pixels that are not of the feature itself.… [C]laim limitation
`[d] … requires selection including pixels having characteristics
`corresponding to the feature, but it does not, however, limit selection
`to only those pixels and others could be included in the selection.”
`
`• Even if the claim were limited to selecting only pixels with
`characteristics of the target, Eriksson and Stringa still disclose
`these limitations
`Petition (Paper 2) at 36–37; Reply (Paper 19) at 18–23; Inst. Dec. (Paper 11) at 16.
`
`40
`
`SAMSUNG EX. 1020
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`
`
`Eriksson Discloses 39[d], [e]
`
`39[c]
`
`“identifying a portion of the image of the face comprising the feature to be detected
`using an anthropomorphic model based on the location of the identified facial
`characteristic”
`
`39[d], [e]
`
`“selecting pixels of the portion of the image having characteristics corresponding to
`the feature to be detected” / “forming at least one histogram of the selected pixels”
`
`“Portion”
`(39[c])
`
`“selected pixels”
`(39[d], [e])
`
`Eriksson
`(Ex. 1005)
`at 315.
`
`Eriksson
`(Ex. 1005)
`at 318.
`
`Petition (Paper 2) at 36–37; Reply (Paper 19) at 18–23.
`
`41
`
`SAMSUNG EX. 1020
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`
`
`Eriksson Discloses 39[d], [e]
`
`39[d], [e]
`
`“selecting pixels of the portion of the image having characteristics corresponding to
`the feature to be detected” / “forming at least one histogram of the selected pixels”
`
`Eriksson selects pixels having “characteristics corresponding to the” pupil
`
`1. Luminance Characteristic: “In order to find the eye-regions given the proceeding
`processing, we rely on the fact that the eyes correspond to intensity-valleys in the
`image.”
`
`2. Positional Characteristic: Eriksson uses “general constraints, such that both eyes
`must be located fairly close to the center of the face”
`
`3. Relationship Characteristic: “We try to find a peak corresponding to a row in the
`image with two connected regions on.”
`• Uses vertical gradient histogram H(y): “Since both eyes are likely to be positioned
`at the same row, H(y) will have a strong peak on that row.”
`
`Petition (Paper 2) at 36; Eriksson (Ex. 1005) at 316; Reply (Paper 19) at 18–22.
`
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`Stringa Discloses 39[d], [e]
`
`39[d], [e]
`
`“selecting pixels of the portion of the image having characteristics corresponding to
`the feature to be detected” / “forming at least one histogram of the selected pixels”
`
`Stringa selects pixels having “characteristics corresponding to the” pupil
`
`“Portion” (39[c])
`
`Stringa (Ex. 1006) at 376.
`
`• Luminance characteristic: The “horizontal
`grey-level distribution” is calculated using the
`thresholding process (which relies on analyzing
`the luminance of each pixel)
`
`PO admits this satisfies PO’s characterization of
`the claim: “pixels with ‘very low luminance
`levels and high gloss’ are selected as these are
`characteristics of a pupil.”
`PO Response (Paper 15) at 40–41.
`
`Petition (Paper 2) at 34–35; PO Response (Paper 15) at 50–51; Reply (Paper 19) at 18–23.
`
`43
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`
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`Obviousness Over Eriksson and Stringa
`
`Motivation to Combine
`
`Eriksson
`
`Stringa
`
`’518 Patent
`
`44
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`Obviousness Over Eriksson and Stringa
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`It would have been obvious to combine Eriksson and Stringa
`• Both use histograms to identify a pupil.
`
`• Eriksson explicitly builds on Stringa.
`
`“One interesting application for face
`recognition was developed by Stringa
`[12]. He used the observation that the
`eyes are regions of rapidly changing
`intensity. We use a similar approach
`on a reduced version of the image.”
`
`“As suggested by Stringa
`[12], we use the observation
`that eye-regions correspond
`to regions of high spatial
`frequency.”
`
`Eriksson (Ex. 1005) at 315 (emphasis added).
`
`Eriksson (Ex. 1005) at 316 (emphasis added).
`
`Petition (Paper 2) at 26–28.
`
`45
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`Obviousness Over Eriksson and Stringa
`
`Contrary to PO’s argument, Eriksson and Stringa use histograms to
`identify the pupil, not template matching:
`
`“Our approach is different. It does not proceed by eye template matching. Rather, an
`algorithm is used based on the exploitation of (a priori) anthropometric information
`combined with the analysis of suitable grey-level distributions [i.e., “histograms”],
`allowing direct localization of both eyes.”
`
`Stringa (Ex. 1006) at 369 (emphases added).
`
`“[W]e need a robust way to determine if the eyes are open or closed; so we developed a
`method that looks at the horizontal histogram across the pupil.”
`
`Eriksson (Ex. 1005) at 317 (emphasis added).
`
`Reply (Paper 19) at 23–24.
`
`46
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`
`Overview of the ’518 Patent
`
`Claim Construction
`
`Instituted Grounds for Review
`Eriksson + Stringa
`Ando + Suenaga
`Ando + Suenaga
`Ando + Stringa
`
`47
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`Overview of Ando
`
`• Discloses a system for
`detecting pupils mounted to
`the dashboard of a car
`
`• Uses threshold calculated
`from histogram to binarize
`the image
`
`• Uses blob analysis on
`binarized image to find pupil
`
`Ando (Ex. 1009) at Cover, Fig. 1; Petition (Paper 2) at 21–26.
`
`48
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`
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`Overview of Suenaga
`
`• Discloses a system for
`detecting drowsy driving by
`analyzing blink rates
`
`• Uses horizontal and vertical
`histograms to identify whether
`the eye is open or closed
`
`Suenaga (Ex. 1007) at Cover, Fig. 61; Petition (Paper 2) at 18–21.
`
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`Ground B: Obviousness Over Ando and Suenaga
`
`PO only disputes:
`
`1. Ando’s and Suenaga’s disclosure of forming
`a histogram “of the selected pixels”
`
`2. Suenaga’s disclosure of “identifying a
`characteristic of the face other than the
`feature to be detected”
`
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`
`
`’518 Patent, Claim 39[d], [e]
`
`[pre]
`
`[a]
`
`[b]
`
`[c]
`
`[d]
`
`[e]
`
`[f]
`
`[g]
`
`
`
`Ex. 1001Ex. 1001
`
`51
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`’518 Patent, Claim 39[d], [e]
`
`39[d], [e]
`
`“selecting pixels of the portion of the image having characteristics corresponding to
`the feature to be detected” / “forming at least one histogram of the selected pixels”
`
`• PO argues that “[n]either reference attempts a histogram of
`only iris, pupil, or cornea pixels”
`
`• This interpretation was rejected by the Board:
`Inst. Dec.: “We do not agree that the claim limitation … precludes selection
`of pixels that are not of the feature itself.… [C]laim limitation [d] … requires
`selection including pixels having characteristics corresponding to the feature,
`but it does not, however, limit selection to only those pixels and others could
`be included in the selection.”
`
`• Even if the claim were limited to selecting only pixels with
`characteristics of the target, Ando and Suenaga still disclose
`these limitations
`
`Petition (Paper 2) at 51–52; Reply (Paper 19) at 25–27; Inst. Dec. (Paper 11) at 16; PO Response (Paper 15) at 57.
`
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`Ando Discloses 39[d], [e]
`
`39[c]
`
`“identifying a portion of the image of the face comprising the feature to be detected
`using an anthropomorphic model based on the location of the identified facial
`characteristic”
`
`39[d], [e]
`
`“selecting pixels of the portion of the image having characteristics corresponding to
`the feature to be detected” / “forming at least one histogram of the selected pixels”
`
`“Portion”
`(39[c])
`
`“selected pixels”
`(39[d], [e])
`
`Ando discloses that a
`“face region . . . is divided
`into smaller neighboring
`regions, or the right half
`and the left half, of the
`face region. . . .”
`
`Pixels are selected in the
`region Sd, where the
`pupil is known to be.
`
`Ando(Ex. 1009) at 38:57-60.
`
`Ando (Ex. 1001) at 3:62-4:15,
`4:33-46, 18:3-14, 35:52-54.
`
`Petition (Paper 2) at 48–52; Reply (Paper 19) at 18–23.
`
`Ando (Ex. 1009) at Fig. 13d.
`
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`
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`Ando Discloses 39[d], [e]
`
`39[d], [e]
`
`“selecting pixels of the portion of the image having characteristics corresponding to the
`feature to be detected” / “forming at least one histogram of the selected pixels”
`
`Ando forms a histogram of Sd:
`“A differential gradation histogram is created from a
`region Sd . . . .”
`
`Ando (Ex. 1009) at 35:52–53.
`
`• PO does not explain why the pixels selected in region Sd
`do not have characteristics of the feature to be detected.
`
`• Each pixel is selected because it has the “characteristic”
`of being located in a place where the pupil is likely to be.
`
`• This is a positional characteristic, just like
`characteristics in the ’518 Patent. Ex. 1001 at 18:58-19:25.
`
`Ando (Ex. 1009) at Fig. 13d.
`
`Petition (Paper 2) at 51–53; Reply (Paper 19) at 25–27.
`
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`Ando Discloses 39[f], [g]
`
`39[f], [g]
`
`“analyzing the at least one histogram over time to identify characteristics of
`the feature to be detected” / “said feature being the iris, pupil, or cornea”
`
`PO argues Ando uses a “non-histogram method to identify
`the pupil”
`• But the claim only requires the histogram be analyzed to
`identify “characteristics” of the pupil, not the pupil itself
`
`• The claim does not require direct detection of the pupil in the
`histogram with no further analysis
`
`Petition (Paper 2) at 53–55; Reply (Paper 19) at 25–26.
`
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`Ando Discloses 39[f], [g]
`
`39[f], [g]
`
`“analyzing the at least one histogram over time to identify characteristics of
`the feature to be detected” / “said feature being the iris, pupil, or cornea”
`
`PO argues Ando uses a “non-histogram method to identify
`the pupil”
`But the histogram is a necessary part of the process of
`identifying the pupils — it sets the threshold THe for identifying
`pixels that are more likely to be pupil pixels.
`Ando explains:
`“The threshold value THe . . . is determined from the histogram.”
`Ando (Ex. 1009) at 35:56-58.
`
`Ando calculates “the threshold value THe for detection of the pupils.”
`Ando (Ex. 1009) at 18:3-4.
`
`Petition (Paper 2) at 53–55; Reply (Paper 19) at 25–26.
`
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`
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`Suenaga Discloses 39[d], [e]
`
`39[c]
`
`“identifying a portion of the image of the face comprising the feature to be detected
`using an anthropomorphic model based on the location of the identified facial
`characteristic”
`
`39[d], [e]
`
`“selecting pixels of the portion of the image having characteristics corresponding to
`the feature to be detected” / “forming at least one histogram of the selected pixels”
`
`“Portion” (39[c])
`
`“rectangular areas . . . are set
`as eye presence areas 32.”
`
`“selected pixels” (39[d], [e])
`
`Selects the “hatched candidate
`areas . . . 35a and 35b . . .
`for an eye presence area”
`
`“histogram” (39[e])
`
`X-histograms . . . 33a and 33b . . .
`are generated” along with
`“Y-histograms . . . 34a and 34b”
`
`Petition (Paper 2) at 48–53; Reply (Paper 19) at 25–27.
`
`Suenaga
`(Ex. 1007)
`at 23:24-27.
`
`Suenaga
`(Ex. 1007)
`at 23:34-35.
`
`Suenaga
`(Ex. 1007)
`at 23:27–34.
`
`Suenaga (Ex. 1007) at Fig. 61.
`
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`Suenaga Discloses 39[d], [e]
`
`39[d], [e]
`
`“selecting pixels of the portion of the image having characteristics corresponding to
`the feature to be detected” / “forming at least one histogram of the selected pixels”
`
`Suenaga selects pixels having “characteristics corresponding to
`the” pupil
`
`1. Arrangement characteristic: Selected pixels must be to the
`sides of the center of the face: “rectangular areas existing in the
`predetermined ranges in the X-direction on the left and right
`sides of this barycenter or centroid 31.” Suenaga (Ex. 1007) at 23:24–
`27.
`
`2. Location characteristic: Selected pixels must be in the
`“hatched candidate areas.” Suenaga (Ex. 1007) at 23:34–35.
`
`PO Response: “A predetermined threshold is used to create the
`black blobs (see figure 61 . . . )”
`
`Suenaga (Ex. 1007) at Fig. 61.
`
`Petition (Paper 2) at 52; Reply (Paper 19) at 22; PO Response (Paper 15) at 60–65.
`
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`
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`’518 Patent, Claim 39[b]
`
`[pre]
`
`[a]
`
`[b]
`
`[c]
`
`[d]
`
`[e]
`
`[f]
`
`[g]
`
`
`
`Ex. 1001Ex. 1001
`
`59
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`
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`’518 Patent, Claim 39[b]
`
`39[b]
`
`“identifying a characteristic of the face other than the feature to be detected”
`
`• PO does not dispute that Ando satisfies this limitation
`
`• Contrary to PO’s arguments, Suenaga discloses this limitation
`
`Petition (Paper 2) at 45–47; Reply (Paper 19) at 27–28.
`
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`Suenaga Discloses 39[b]
`
`39[b]
`
`“identifying a characteristic of the face other than the feature to be detected”
`
`• Suenaga finds “the barycenter or centroid
`31 from the average of the coordinates of
`black pixels in the binary image 30,” i.e.,
`the eyes, eyebrows, nostrils, and mouth.
`Suenaga (Ex. 1007) at 23:21–24
`
`• It is the center of the face and
`approximate location of the nose.
`
`Petition (Paper 2) at 47; Reply (Paper 19) at 27–28.
`
`Suenaga (Ex. 1007) at Fig. 61.
`
`61
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`Suenaga Discloses 39[b]
`
`39[b]
`
`“identifying a characteristic of the face other than the feature to be detected”
`
`Consistent with the ’518 Patent:
`
`“While the invention is being described with
`respect to identification of the nostrils as a
`starting point to locating the eyes, it is foreseen
`that any other facial characteristic, e.g.,
`the nose, ears, eyebrows, mouth, etc., and
`combinations thereof, may be detected
`as a starting point for locating the eyes.”
`
`Petition (Paper 2) at 47; Reply (Paper 19) at 3–5, 27–28.
`
`62
`
`Suenaga (Ex. 1007) at Fig. 61.
`
`SAMSUNG EX. 1020
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`
`
`Obviousness Over Ando and Suenaga
`
`Motivation to Combine
`
`Ando
`
`Suenaga
`
`’518 Patent
`
`63
`
`SAMSUNG EX. 1020
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`
`
`Obviousness Over Ando and Suenaga
`
`It would have been obvious to combine Ando and Suenaga
`Suenaga improves Ando:
`• Suenaga’s X and Y histograms can
`increase Ando’s detection accuracy
`• Helps distinguish between eyebrow and eye
`• Helps identify whether eye is opened or closed
`
`Same field of endeavor:
`• Both use image processing, including histograms,
`to identify an eye
`• Suenaga cites the Ueno patent, and Ueno cites Ando
`
`Petition (Paper 2) at 41–44; Reply (Paper 19) at 28–30; Hart Decl. (Ex. 1002), ¶¶ 113–116.
`
`64
`
`Suenaga (Ex. 1007) at Fig. 61.
`
`SAMSUNG EX. 1020
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`
`
`Obviousness Over Ando and Suenaga
`
`Contrary to PO’s argument, a POSA would seek to further increase Ando’s
`accuracy, which is admittedly imperfect:
`
`“This series of operations for detecting [the pupils and mouth] is repeated up to 8 times. If they cannot
`be detected in spite of 8 series of operations, the processes (l)-(8) are carried out to
`determine new threshold values . . . .” Ando (Ex. 1009) at 36:45–51.
`
`PO’s argument is irrelevant – Suenaga improves Ando by distinguishing between
`the eyebrow and eye and identifying blink rates, not by detecting the pupil
`
`Petition (Paper 2) at 41–44; Reply (Paper 19) at 28–30; Hart Decl. (Ex. 1002), ¶¶ 113–116.
`
`65
`
`Suenaga (Ex. 1007) at Fig. 2.
`
`SAMSUNG EX. 1020
`
`
`
`Overview of the ’518 Patent
`
`Claim Construction
`
`Instituted Grounds for Review
`Eriksson + Stringa
`Ando + Suenaga
`Ando + Stringa
`Ando + Stringa
`
`66
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`
`
`Ground C: Obviousness Over Ando and Stringa
`
`PO only disputes:
`
`1. Stringa’s disclosure of a “histogram”
`
`2. Ando’s and Stringa’s disclosure of forming a
`histogram “of the selected pixels”
`
`67
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`
`
`Obviousness Over Ando and Stringa
`
`Motivation to Combine
`
`Ando
`
`Stringa
`
`’518 Patent
`
`68
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`
`
`Obviousness Over Ando and Stringa
`
`It would have been obvious to combine Ando and Stringa
`Stringa improves Ando:
`• Ando admittedly fails to detect the
`pupil in some situations
`• Stringa’s advanced horizontal
`histogram method would help
`Ando find the pupil
`
`Same field of endeavor:
`• Both use image processing,
`including histograms, to
`identify a pupil
`• Both explicitly use
`“anthropomorphic” models
`
`Stringa (Ex. 1006) at Fig. 8
`
`Petition (Paper 2) at 56–58; Hart Decl. (Ex. 1002), ¶¶ 137–139.
`
`69
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`
`
`Thank You
`Thank You
`
`70
`SAMSUNG EX. 1020 W
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`SAMSUNG EX. 1020
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`
`
`CERTIFICATE OF SERVICE
`
`The undersigned certifies pursuant to 37 C.F.R. § 42.6(e) and § 42.105 that
`
`on June 25, 2018, a true and correct copy of SAMSUNG’S
`
`DEMONSTRATIVES was served via electronic mail on Counsel for the Patent
`
`Owner at the following address of record:
`
`Michael N. Zachary (pro hac vice)
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