Ex Parte Niehsen et al

Patent Trial and Appeal Board

Nov 30, 2016

13000282 (P.T.A.B. Nov. 30, 2016)

United States Patent and Trademark Office
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
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Alexandria, Virginia 22313-1450
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APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO.
13/000,282 03/17/2011 Wolfgang Niehsen 10191/6560 1891
24972 7590 12/02/2016
NORTON ROSE FULBRIGHT US LLP
1301 Avenue of the Americas
NEW YORK, NY 10019-6022
EXAMINER
HILL, SCHILLER D
ART UNIT PAPER NUMBER
2614
NOTIFICATION DATE DELIVERY MODE
12/02/2016 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):
nyipdocket@nortonrosefulbright.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte WOLFGANG NIEHSEN and STEPHAN SIMON
Appeal 2015-005025
Application 13/000,2821
Technology Center 2600
Before ALLEN R. MacDONALD, JASON V. MORGAN, and
HUNG H. BUI, Administrative Patent Judges.
BUI, Administrative Patent Judge.
DECISION ON APPEAL
Appellants seek our review under 35 U.S.C. § 134(a) of the
Examiner’s Final Office Action rejecting claims 12—17, 19—23, and 25—32,
which are all of the claims pending on appeal. Claims 1—11, 18, and 24 are
cancelled. We have jurisdiction under 35 U.S.C. § 6(b).
We AFFIRM.2
1 According to Appellants, the real party in interest is Robert Bosch GmbH.
App. Br. 1.
2 Our Decision refers to Appellants’ Appeal Brief filed September 24, 2014
(“App. Br.”); Reply Brief filed April 2, 2015 (“Reply Br.”); Examiner’s
Answer mailed February 3, 2015 (“Ans.”); Final Office Action mailed May
29, 2014 (“Final Act.”); and original Specification filed December 20, 2010
(“Spec.”).
Appeal 2015-005025
Application 13/000,282
STATEMENT OF THE CASE
Appellants’ invention relates to a method for visualizing image data
including a plurality of pixel values for a plurality of pixels, and including,
for each of at least a subset of the plurality of pixels, a respective piece of
additional information indicating a characteristic of the respective pixel,
besides for the pixel value of the respective pixel. Sub. Spec. 1:5—7;
Abstract. According to Appellants, the additional information represents a
gradual change of the characteristic between neighboring pixels. Sub. Spec.
3:27—32, 4:14—18, Fig. 2. In particular, the additional information is
superimposed over image data and can be displayed based on a certain
classification (e.g., a difference in coloration, texture, brightness, darkening,
sharpening, magnification, increased contrast, reduced contrast, omission,
virtual illumination, inversion, distortion, abstraction, with contours, in a
chronological variable manner (moving, flashing, vibrating, wobbling)) in a
manner that is easier for the user to comprehend. Spec. 3:1—11.
Claims 12, 19, 20, and 23 are independent. Claim 12 is illustrative of
Appellants’ invention, as reproduced with disputed limitations emphasized:
12. A method for visualizing image data including a plurality
of pixel values for a plurality of pixels, and including, for each
of at least a subset of the plurality of pixels, a respective piece
of additional information indicating a characteristic of the
respective pixel, besides for the pixel value of the respective
pixel, the method comprising:
representing the image data as an image data image
having pixels whose characteristics are determined based on (a)
the pixel values, and (b), for each of the at least the subset of
the plurality of pixels, modification of the respective pixel
value according to the respective characteristic indicated for the
respective pixel by the respective additional piece of
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Application 13/000,282
information of the respective pixel;
wherein the additional information represents a gradual
change of the characteristic between neighboring pixels.
App. Br. 9 (Claims App’x.).
Examiner’s Rejections and References
(1) Claims 12—15, 19—23, and 25—32 stand rejected under 35
U.S.C. § 103(a) as being unpatentable over Auty et al., (US 5,809,161;
issued Sept. 15, 1998 (“Auty”)), Stefan Vacek et al., Road-Marking Analysis
for Autonomous Vehicle Guidance', Institute for Computer Science and
Engineering, University of Karlsruhe (“Vacek”)), and Wided Miled et al.,
Robust Obstacle Detection Based on Dense Disparity Maps, Computer
Aided Systems Theory-EUROCAST 2007, 1142—50 (“Miled”). Final Act.
3-16.
(2) Claims 16 and 17 stand rejected under 35 U.S.C. § 103(a) as
being unpatentable over Auty, Vacek, Miled, and Doug DeCarlo and
Anthony Santella, Stylization and abstraction of photographs, ACM
Transactions on Graphics (TOG), vol. 21, no. 3, 769-76 (2002) (“DeCarlo”).
Final Act. 16—19.
ISSUE
Based on Appellant’s arguments, the dispositive issue presented on
appeal is whether the Examiner erred in finding the cited prior art teaches or
suggests the disputed limitations: (1) “wherein the additional information
represents a gradual change of the characteristic between neighboring
pixels”; (2) “a respective piece of additional information indicating a
characteristic of the respective pixel”; and (3) “additional information
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Application 13/000,282
indicating a characteristic of the respective pixel, besides for the pixel value
of the respective pixel,” as recited in each of Appellants’ independent claims
12, 19, 20, and 23. App. Br. 4—7; Reply Br. 2-4.
ANALYSIS
With respect to independent claim 12, the Examiner finds Auty
teaches Appellants’ claimed
method for visualizing image data including a plurality of
pixel values for a plurality of pixels, and including, for each of
at least a subset of the plurality of pixels, a respective piece of
additional information indicating a characteristic of the
respective pixel, besides for the pixel value of the respective
pixel.
Final Act. 4—5 (citing Auty, 10:63—66, 11:24-45, Fig. 16).
According to the Examiner, Auty’s Figure 16 teaches “the image data
having pixels as all displayed images have pixels, and the displayed image is
enriched over the original image by superimposing boxes around vehicles
and a histogram,” i.e., “superimposed with cluster markings and other data.”
Final Act. 4 (citing Auty, 12:11—26, Fig. 16).
Auty’s Figure 16 is reproduced below:
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Application 13/000,282
Auty’s Figure 16 depicts a real time status display having a live image
superimposed with cluster markings and other data.
The Examiner does not rely on Auty as teaching or suggesting the
alternative image enhancement feature of:
pixels [of image data] whose characteristics are determined
based on (a) the pixel values, and (b) for each of the at least
subset of the plurality of pixels, modification of the respective
pixel value according to the respective characteristic indicated
for the respective pixel by the respective additional piece of
information of the respective pixel.
Final Act. 5.
Rather, the Examiner relies on Vacek’s teaching of overlying images
with additional information to highlight the meaningful visual elements with
regards to a vehicle to teach or suggest this feature. Id. at 5—6 (citing Vacek
Fig. 14).
The Examiner further relies on the disparity maps of Miled in
combination with Auty and Vacek to teach or suggest “[wl herein the
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Application 13/000,282
additional information represents a gradual change of the characteristic
between neighboring pixels” to provide “a visualization that highlights the
distance and location of important road features” and “to aid in the
avoidance of possible collisions.” Final Act. 5—8 (citing Vacek’s Fig. 14;
Miled’s Fig. 2, Abstract).
Appellants present several arguments against the Examiner’s
combination. First, Appellants argue the cited art, including Auty, Vacek,
and Miled, does not teach that “the additional information represents a
gradual change of the characteristic between neighboring pixels,” as recited
in claims 12, 19, 20, and 23. App. Br. 4—5; Reply Br. 1^4. In particular,
Appellants acknowledge Miled teaches “a vision-based obstacle detection
method that relies on dense disparity estimation between a pair of stereo
images and involves computation of a depth map,” but argues (1) “nowhere
does Miled disclose or suggest that the disparity maps represent a gradual
change in depth between neighboring pixels,” as recited in claims 12, 19, 20,
and 23, and (2) “the two corresponding points in a pair of stereo images [of
Miled] cannot be considered neighboring pixels” and “pixels of different
images [as described by Miled] are not neighbors.” App. Br. 4—5; Reply Br.
2-3.
Second, Appellants argue the cited art does not teach “a respective
piece of additional information indicating a characteristic of the respective
pixel,” as recited in each of Appellants’ independent claims 12, 19, 20, and
23. App. Br. 4—6; Reply Br. 2—3. In particular, Appellants argue: (1)
“Auty’s classification and labeling of pixel blobs” is not the same as the
claimed “respective piece of additional information indicating a
characteristic of the respective pixel,” as recited in Appellants’ claims, and
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(2) “one of ordinary skill in the art would not be motivated to combine Auty
and Miled in the manner suggested by the Examiner” because Auty’s
“binary representation (namely a black and white representation of an
image)... is not suitable for representing gradations of depth,” as disclosed
by Miled. App. Br. 5—6. According to Appellants, “the cluster marking of
Auty is not suitable for annotating the depth map of Miled” because “the
cluster markings (e.g., speed of the vehicle) is more accurately computed
from a live image rather than the depth map approximation of Miled.”
Reply Br. 3.
Third, Appellants further argue the cited art does not teach “additional
information indicating a characteristic of the respective pixel, besides for
the pixel value of the respective pixelf as recited in each of Appellants’
independent claims 12, 19, 20, and 23. App. Br. 6—7; Reply Br. 3^4. In
particular, Appellants argue Auty’s histogram, shown in Figure 16, “refers to
a graph whose bars indicate, for each of a plurality of grey level values, the
number of pixels having that value” and, as such, “does not provide
additional information about an individual pixel other than the pixel’s pixel
value.” App. Br. 6 (citing Auty 11:1—4). Similarly, Appellants argue Auty’s
“boxes refer to the drawing of an outline of the portion of an image
determined to include a vehicle,” and, as such, “are not information that
indicate a characteristic of an individual pixel, which is then used for
modification of the pixel value.” Id. at 6—7 (citing Auty Fig. 15).
We do not find Appellants’ arguments persuasive. Instead, we find
the Examiner has provided a comprehensive response to Appellants’
arguments supported by a preponderance of evidence. Ans. 2—8. As such,
we adopt the Examiner’s findings and explanations provided therein. Id.
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For additional emphasis, we note all the cited references disclose similar
techniques of visualizing “image data” having some form of “additional
information” superimposed or overlaid on the “image data” in a manner that
is easier for the user to comprehend, as is also disclosed by Appellants’
disclosure.
For example, Auty teaches visualizing “image data” having
“additional information” superimposed thereon in the form of cluster
markings and other data (i.e., histogram or boxes). Auty 11:24—45, Fig. 16.
Similarly, Vacek also teaches visualizing “image data” having “additional
information” superimposed thereon in the form of road markings to avoid
accident or collision. Vacek’s Fig. 14. Vacek further teaches that “road
markings have different brightness at different distances” relative to a
vehicle. Vacek p. 2. According to Vacek, “markings are overlaid with short
red bars.” Vacek’s Fig. 14. Likewise, Miled teaches visualizing “image
data” having “additional information” superimposed thereon in the form of
disparity images, shown in Figure 2 and Figure 4. According to Miled,
disparity maps are used to account for “possible illumination change” or
“brightness changes between both images [of a scene] in the stereo pair [i.e.,
pair of left and right views of the same scene].” Miled 1143, 1145.
As recognized by Appellants, “[t]he depth map of. . . (Miled: fig. 2
and fig. 4) represents a gradual change of depth in the identification and
marking of objects that are [considered as] obstacles.” Ans. 3 (citing
Miled’s Figs. 2 and 4).
Miled’s Figure 23 is reproduced below:
3 Miled’s Figure 2 (black/white image) and Figure 4 (color image) are
reproduced directly from Wided Miled et al., Robust Obstacle Detection
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Application 13/000,282
Miled’s Figure 2 shows disparity estimation (i.e., computed disparity maps
shown below) for corresponding images (shown on top) of a scene acquired
in different situations.
As shown in Miled’s Figure 2, the depth map (additional information)
represents a gradual change of the characteristic (depth) in the marking of
objects, i.e., “change of the characteristic between neighboring pixels [of an
image scene].” The gradualness of such change is apparent in the lack of
definition in the computed disparity maps in areas where there are sharp
changes in depth (e.g., in the outlines of the people captured in the images).
Miled’s Figure 4 is reproduced below:
Based on Dense Disparity Maps, Computer Aided Systems Theory-
EUROCAST 2007, 1142—50, available, via Internet, at
link, springer, com/content/p df.
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Application 13/000,282
Miled’s Figure 4 shows classification of stereo points from disparity images.
As shown in Miled’s Figure 4, different colors can be assigned to
different types of (1) “pixels belonging to the road surface” and (2) “those
[pixels] belonging to obstacles based on the depth map.” See Miled 1149.
Contrary to Appellants’ arguments, the two images disclosed by Miled are a
pair of left and right views of the same scene (image). As such, pixels as
described by Miled are neighboring pixels of the same scene (image).
In our view, the use of “additional information” to superimpose on
“image data” is well known, whether for (1) cluster markings and other data
(i.e., histogram or boxes) as disclosed by Auty, (2) road markings with
“different brightness at different distances” as disclosed by Vacek, or (3)
disparity images as disclosed by Miled. As such, any effort to incorporate
these features as part of Auty’s method of visualizing “image data” with
“additional information” would have been obvious to those skilled in the art
because these well-known features perform the same known function and
yield no more than one would expect otherwise. See KSR Int 7 Co. v.
Teleflex Inc., 550 U.S. 398, 406 (2007). A skilled artisan would “be able to
fit the teachings of multiple patents together like pieces of a puzzle” since
the skilled artisan is “a person of ordinary creativity, not an automaton.” Id.
at 420-21.
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Lastly, we note Appellants have not demonstrated the Examiner’s
proffered combination of references would have been “uniquely challenging
or difficult for one of ordinary skill in the art.” See Leapfrog Enters., Inc. v.
Fisher-Price, Inc., 485 F.3d 1157, 1162 (Fed. Cir. 2007) (citing KSR, 550
U.S. at 418). Nor have Appellants provided objective evidence of secondary
considerations which our reviewing court guides “operates as a beneficial
check on hindsight.” Cheese Systems, Inc. v. Tetra Pak Cheese and Powder
Systems, Inc., 725 F.3d 1341, 1352 (Fed. Cir. 2013).
For these reasons, we sustain the Examiner’s obviousness rejection of
independent claims 12, 19, 20, and 23, and their respective dependent claims
13—17, 21, 22, and 25—32, which Appellants do not argue separately. App.
Br. 7.
CONCFUSION
On the record before us, we conclude Appellants have not
demonstrated the Examiner erred in rejecting claims 12—17, 19—23, and 25—
32 under 35 U.S.C. § 103(a).
DECISION
As such, we AFFIRM the Examiner’s final rejection of claims 12—17,
19-23, and 25-32.
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a)(l)(iv).
AFFIRMED
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