Ex Parte Kolarov et al

Patent Trial and Appeal Board

Jun 20, 2018

15137998 (P.T.A.B. Jun. 20, 2018)

UNITED STA TES p A TENT AND TRADEMARK OFFICE
APPLICATION NO. FILING DATE
15/137,998 04/25/2016
81310 7590 06/22/2018
Meyertons, Hood, Kivlin, Kowert & G (Apple)
P.O. BOX 398
Austin, TX 78767-0398
FIRST NAMED INVENTOR
Krasimir D. Kolarov
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
Address: COMMISSIONER FOR PATENTS
P.O. Box 1450
Alexandria, Virginia 22313-1450
www .uspto.gov
ATTORNEY DOCKET NO. CONFIRMATION NO.
5888-96301 5335
EXAMINER
TEITELBAUM, MICHAELE
ART UNIT PAPER NUMBER
2422
NOTIFICATION DATE DELIVERY MODE
06/22/2018 ELECTRONIC
Please find below and/or attached an Office communication concerning this application or proceeding.
The time period for reply, if any, is set in the attached communication.
Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the
following e-mail address(es):
patent_docketing@intprop.com
ptomhkkg@gmail.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte KRASIMIR D. KOLAROV and
STEVEN E SAUNDERS
Appeal2017-011734
Application 15/137,998 1
Technology Center 2400
Before BARBARA A. BENOIT, AMBER L. HAGY, and
PHILLIP A. BENNETT, Administrative Patent Judges.
BENNETT, Administrative Patent Judge.
DECISION ON APPEAL
STATEMENT OF THE CASE
Appellants appeal under 35 U.S.C. § 134(a) from the Examiner's final
rejection of claims 10-13, 21-24, 26-33, and 35. 2 We have jurisdiction
under 35 U.S.C. § 6(b ).
We reverse.
1 Appellants' Brief ("App. Br.") identifies Apple, Inc., as the real party in
interest. App. Br. 2.
2 Claims 14, 25, and 34 are objected to as being dependent upon a rejected
base claim, but indicated to be otherwise allowable.
Appeal 2017-011734
Application 15/137,998
CLAIMED SUBJECT MATTER
The claims are directed to analyzing image quality when capturing or
streaming video. Spec. ,r 22. For example, embodiments of the invention
allow a mobile phone user to receive notification that video quality has
fallen below a threshold in real-time, without needing reference images for
comparison and/or evaluation. Spec. ,r,r 27, 33. In order to provide accurate
feedback without the use of any reference image, an image content scenario
is determined for a captured image, with "[ a ]n example of an exploitable
scenario is the presence of a human face" (Spec. ,r 35), and other examples
including "recognition of an outdoor landscape, with blue sky, green foliage,
and brown ground" (Spec. ,r 36).
Quality-checking heuristics are defined that are specific to these
scenarios. These scenario-specific heuristics are configured to check for
high contrasts and specific details that would be characteristic of the
identified scenario. For example, in the "human face" scenario, the "the
scenario recognition module may be configured to apply a heuristic in
accordance with finding high contrasts and sharp detail in the facial area and
to report video quality problems if those characteristics are not found."
Spec. ,r 35. Similarly, in the "landscape" scenario, the heuristic model may
"look[] for relatively featureless blue above highly textured green" or may
"emphasize detail sharpness is the foliage areas." Spec. ,r 36. Claim 10,
reproduced below, is illustrative of the claimed subject matter:
10. A method, comprising:
performing, by one or more computing devices having one
or more processors:
obtaining an image;
evaluating the image to determine an image content
scenario for the image;
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Appeal 2017-011734
Application 15/137,998
selecting a heuristic set from among a plurality of
scenario-specific heuristic sets, wherein each scenario-specific
heuristic set corresponds to a different image content scenario,
wherein said selecting is based on the determined image content
scenano;
analyzing the image with the selected scenario-specific
heuristic set to determine one or more image quality metric
measurements for the image; and
outputting the one or more image quality metric
measurements.
App. Br. 20 (Claims Appendix).
REFERENCES
The prior art relied upon by the Examiner in rejecting the claims on
appeal is:
Ali
Gohara
Agrawala
Obrador
Bergman
US 2002/0168010 Al
US 2005/0238321 Al
US 2006/0200759 Al
US 2008/0019661 Al
US 2012/0033875 Al
REJECTIONS
Nov. 14, 2002
Oct. 27, 2005
Sept. 7, 2006
Jan.24,2008
Feb.9,2012
Claims 10, 12, 13, 21, 22, 28-31, and 35 stand rejected under
35 U.S.C. § 103 as being unpatentable over Gohara and Ali. Final Act. 2-8.
Claims 11, 23, 24, 32, and 33 stand rejected under 35 U.S.C. § 103 as
being unpatentable over Gohara, Ali, and Agrawala. Final Act. 8-10.
Claim 26 stands rejected under 35 U.S.C. § 103 as being unpatentable
over Gohara, Ali, and Obrador. Final Act. 10-11.
Claim 27 stands rejected under 35 U.S.C. § 103 as being unpatentable
over Gohara, Ali, and Bergman. Final Act. 11-12.
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Appeal 2017-011734
Application 15/137,998
ISSUE
Has the Examiner erred in finding Ali teaches "analyzing the image
with the selected scenario-specific heuristic set to determine one or more
image quality metric measurements for the image," as recited in claim 10?3
ANALYSIS
In rejecting claim 10, the Examiner finds Gohara teaches the
"evaluating" and "selecting" steps, while Ali teaches the "analyzing" and
"outputting" steps. Final Act. 3--4. More specifically, and relevant to this
issue, the Examiner finds Ali teaches the use of a heuristic algorithm "in a
looping process to determine quality of video after video processing is
performed." Final Act. 4 ( citing Ali, Figure 1 ).
Appellants argue the Examiner has erred because the heuristics
described in Ali are used to find optimization parameters, and they are not
used to determine an image quality metric. App. Br. 10-11; Reply Br. 4. In
particular, Appellants argue the heuristic algorithm "is part of an
optimization unit that takes an already-existing objective quality metric unit
as input and produces configuration parameters for video processing
algorithms that process the video." Reply Br. 5. We agree.
Ali is directed to "efficiently configuring video-processing algorithms
in order to provide a high quality video image." Ali ,r 14. It teaches the use
of an "optimization unit 120 [that] includes genetic algorithm 122 and
heuristic algorithm 124." Ali ,r 28. The optimization unit 120 receives input
from an objective quality metric unit 130 which "provides a scalable
3 Because this issue is dispositive of the rejections before us, we do not
consider other issues raised by Appellants.
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Appeal 2017-011734
Application 15/137,998
dynamic objective metric for automatically evaluating video quality." Id. at
,r 27. Thus, the component in Ali that provides an image quality assessment
or measurement is the objective quality metric unit 130, and not the heuristic
algorithm 124. Ali further teaches the objective quality metric unit inputs its
image quality measurement to the optimization unit 120, which includes the
heuristic algorithm 124. Ali ,r 28. This description is confirmed by the
depiction of the data flow shown in Figure 1, which shows the output of the
objective quality metric unit 130 being received as input to the optimization
unit 120. See Ali, Fig. 1.
As such, we agree with Appellants that the heuristic algorithm 124 in
Ali does not analyze the image "to determine one or more image quality
metric measurements" ( emphasis added), but instead receives image quality
metric measurements as input from objective quality metric unit 130. As
explained by Ali, "[a]s the heuristic algorithm ... is applied, the parameters
are adjusted" in order to identify the best video optimization parameters for
the video signal. Ali ,r,r 51-52.
Accordingly, we are persuaded the Examiner has erred in finding Ali
teaches or suggests the recited "analyzing" step in claim 10, and we do not
sustain its rejection. For the same reasons, we also do not sustain the
rejections of independent claims 21 and 30, which recite substantially
similar limitations. The remaining appealed claims depend from one of
independent claims 10, 21, and 31 and, therefore, stand with their respective
independent claims.
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Appeal 2017-011734
Application 15/137,998
DECISION
We reverse the Examiner's rejection of claims 10-13, 21-24, 26-33,
and 35.
REVERSED
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