DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
In response to applicant’s amendment received on 3/2/26, all requested changes to the claims have been entered. Claims 1-20 were previously pending. Claims 21-33 have been added. Claims 8-20 have been cancelled. Claims 1-7 and 21-33 are currently pending.
Election/Restrictions
Applicant’s election without traverse of Group I (claims 1-7) in the reply filed on 3/2/26 is acknowledged. Claims 8-20, associated with Group II, have been cancelled.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-7 and 21-33 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 1, the phrase “that have not been previously swept” in lines 8-9, is indefinite. Specifically, the term “swept” appears to refer to previously limitation “the raster search comprising alternating between sweeping left to right and then up and down systematically”. However the alternative spiral search is defined as comprising “a circumferential-direction scanning”. Therefore it’s unclear if the limitation in question, which uses the word “swept”, is only referring to a situation in which a raster search is previously conducted or if it is actually meant to refer to a situation in which either of the raster and spiral searches was previously conducted. If it is the later, then perhaps changing the limitation to “swept or scanned” would be appropriate.
Claims 2-7 are rejected by the virtue of their dependency upon rejected claim 1 above.
Regarding claim 3, the limitation “not previously scanned” is indefinite. Claim 1, lines 8-9, uses the phrase “that have not been previously swept”. Use of the word “scanned” makes it unclear if the limitation in question is referring to that limitation of claim 1, or, as similarly discussed with regards to claim 1, if it is only referring to a situation in which a spiral search is previously conducted. Since it uses the word “scanned” which is associated with the spiral search and not the raster search. Or, if it is actually meant to refer to a situation in which either of the raster and spiral searches was previously conducted. If it is the later, then perhaps changing the limitation to “swept or scanned” would be appropriate.
Claim 3 recites the limitation "the lowest range value" in line 2-3. There is insufficient antecedent basis for this limitation in the claim.
Claims 4-6 are rejected by the virtue of their dependency upon rejected claim 3 above.
Claim 21, lines 9-10, also recites the indefinite limitation “that have not been previously swept” and is rejected for the same reasoning indicated above with regards to claim 1.
Claims 22-27 are rejected by the virtue of their dependency upon rejected claim 21.
Claim 23 recites the same indefinite limitations as discussed above with regards to claim 3, and is therefore rejected for the same reasoning indicated above with regards to claim 3.
Claims 24-26 are rejected by the virtue of their dependency upon rejected claim 23 above.
Claim 28, lines 9-10, also recites the indefinite limitation “that have not been previously swept” and is rejected for the same reasoning indicated above with regards to claim 1.
Claims 28-33 are rejected by the virtue of their dependency upon rejected claim 28.
Claim 30 recites the same indefinite limitations as discussed above with regards to claim 3, and is therefore rejected for the same reasoning indicated above with regards to claim 3.
Claims 31-33 are rejected by the virtue of their dependency upon rejected claim 30 above.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 2, 21, 22, 28 and 29 are rejected under 35 U.S.C. 103 as being unpatentable over US 2023/0288201 to Niklaus et al. (“Niklaus”) in view of USPN 5,615,287 to Fu et al. (“Fu”).
Regarding claim 1, Niklaus discloses a method for object abstraction to distinguish between different objects in a depth map generated from a time-of-flight sensor (Fig. 2; Fig. 3; Abstract, paragraphs 27 and 38, wherein edges are distinguished between different objects in point cloud data (i.e. depth map) generated from a time-of-flight sensor), the method comprising:
conducting a paragraphs 38, 71-74, wherein a search for object edges is conducted on the point cloud (i.e. depth map)),
detecting edges of an object (paragraphs 38, 71-74, wherein an object edges are detected on the point cloud (i.e. depth map))
calculating one or more high-level parameters related to the object (paragraphs 38, 47-49 and 87, wherein high-level parameters (e.g. bending radius of the edge, length/size of the edge, etc.) are calculated based on a merit function); and
repeating the paragraphs 38 and 47, wherein the process of searching for object edges is repeated corresponding to searching for cells that have not been “swept” (i.e. searched) to identify other edges (i.e. similar objects)).
As indicated by the double strike throughs above, Niklaus does not disclose expressly that the search on the depth map is a raster or spiral search, that the raster search comprising alternating between sweeping left to right and then up and down systematically, the spiral search comprising a circumferential-direction scanning, and detecting edges of an object to guide a continuation of the raster or spiral search.
Fu discloses a method for object abstraction to distinguish between different objects in an image (Figs. 5, 6, 10, column 10, lines 9-60 and column 12, line 19 – column 13, line 8, wherein edges are distinguished between different objects in an image), the method comprising:
conducting a raster or spiral search on the image, the raster search comprising alternating between sweeping left to right and then up and down systematically, the spiral search comprising a circumferential-direction scanning (Figs. 10 and column 12, line 19 – column 13, line 8, wherein edges are searched for using both raster and spiral methods disclosed in the claim);
detecting edges of an object to guide a continuation of the raster or spiral search (Figs. 10 and column 12, line 19 – column 13, line 8, wherein the detection of an object edge guides the continuation of the search direction, using the raster and/or spiral search disclosed, to trace the object); and
repeating the raster or spiral search for cells of the image that have not been previously swept to similarly identify other objects (Figs. 10 and column 12, line 19 – column 13, line 8, wherein the search is repeated for each edge pixel not previously swept using the raster and/or spiral search).
Niklaus & Fu are combinable because they are from the same art of image processing, specifically edge detection.
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to incorporate a raster and/or spiral search for object edge detection, the raster search comprising alternating between sweeping left to right and then up and down systematically, the spiral search comprising a circumferential-direction scanning, and using detected edges of an object to guide a continuation of the raster and/or spiral search, as taught by Fu, into the process of detecting edges in a point cloud (i.e. depth map) for distinguishing being different objects as disclosed by Niklaus.
The suggestion/motivation for doing so would have been to provide simple and quick image processing techniques such as detecting edge pixels based on adjacent pixels and a local derivative (Fu, column 3, lines 40-46 and column 4, lines 1-8) .
Therefore, it would have been obvious to combine Fu with Niklaus to obtain the invention as specified in claim 1.
Regarding claim 2, the combination of Niklaus and Fu discloses the method of claim 1, wherein the one or more high-level parameters of the object comprises a center, a size, a minimum range, a median range, a maximum range, a reflectance, OR a combination thereof (Niklaus, paragraphs 38, 47-49 and 87, wherein high-level parameters (e.g. length of the edge (i.e. “size”) or mean intensity (i.e. “reflectance” )) are calculated based on a merit function).
Regarding claim 21, Niklaus discloses a time-of-flight circuit (Fig. 1a, 1b; paragraphs 27, 60, element “10” corresponding to a time-of-flight sensor and element “30” the “computing unit” corresponding to a controller) for object abstraction to distinguish between different objects in a depth map generated from a time-of-flight sensor (Fig. 2; Fig. 3; Abstract, paragraphs 27 and 38, wherein edges are distinguished between different objects in point cloud data (i.e. depth map) generated from a time-of-flight sensor), the time-of-flight circuit comprising a controller couplable to the time-of-flight sensor, the controller configured to:
conducting a paragraphs 38, 71-74, wherein a search for object edges is conducted on the point cloud (i.e. depth map)),
detecting edges of an object (paragraphs 38, 71-74, wherein an object edges are detected on the point cloud (i.e. depth map))
calculating one or more high-level parameters related to the object (paragraphs 38, 47-49 and 87, wherein high-level parameters (e.g. bending radius of the edge, length/size of the edge, etc.) are calculated based on a merit function); and
repeating the paragraphs 38 and 47, wherein the process of searching for object edges is repeated corresponding to searching for cells that have not been “swept” (i.e. searched) to identify other edges (i.e. similar objects)).
As indicated by the double strike throughs above, Niklaus does not disclose expressly that the search on the depth map is a raster or spiral search, that the raster search comprising alternating between sweeping left to right and then up and down systematically, the spiral search comprising a circumferential-direction scanning, and detecting edges of an object to guide a continuation of the raster or spiral search.
Fu discloses a technique for object abstraction to distinguish between different objects in an image (Figs. 5, 6, 10, column 10, lines 9-60 and column 12, line 19 – column 13, line 8, wherein edges are distinguished between different objects in an image), the method comprising:
conducting a raster or spiral search on the image, the raster search comprising alternating between sweeping left to right and then up and down systematically, the spiral search comprising a circumferential-direction scanning (Figs. 10 and column 12, line 19 – column 13, line 8, wherein edges are searched for using both raster and spiral methods disclosed in the claim);
detecting edges of an object to guide a continuation of the raster or spiral search (Figs. 10 and column 12, line 19 – column 13, line 8, wherein the detection of an object edge guides the continuation of the search direction, using the raster and/or spiral search disclosed, to trace the object); and
repeating the raster or spiral search for cells of the image that have not been previously swept to similarly identify other objects (Figs. 10 and column 12, line 19 – column 13, line 8, wherein the search is repeated for each edge pixel not previously swept using the raster and/or spiral search).
Niklaus & Fu are combinable because they are from the same art of image processing, specifically edge detection.
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to incorporate a raster and/or spiral search for object edge detection, the raster search comprising alternating between sweeping left to right and then up and down systematically, the spiral search comprising a circumferential-direction scanning, and using detected edges of an object to guide a continuation of the raster and/or spiral search, as taught by Fu, into the process of detecting edges in a point cloud (i.e. depth map) for distinguishing being different objects as disclosed by Niklaus.
The suggestion/motivation for doing so would have been to provide simple and quick image processing techniques such as detecting edge pixels based on adjacent pixels and a local derivative (Fu, column 3, lines 40-46 and column 4, lines 1-8) .
Therefore, it would have been obvious to combine Fu with Niklaus to obtain the invention as specified in claim 21.
Regarding claim 22, the combination of Niklaus and Fu discloses the time-of-flight circuit of claim 21, wherein the one or more high-level parameters of the object comprises a center, a size, a minimum range, a median range, a maximum range, a reflectance, or a combination thereof (Niklaus, paragraphs 38, 47-49 and 87, wherein high-level parameters (e.g. length of the edge (i.e. “size”) or mean intensity (i.e. “reflectance” )) are calculated based on a merit function).
Regarding claim 28, Niklaus discloses a device, comprising:
a time-of-flight sensor configured to generate a depth map (Fig. 1a, 1b, 2, element 10; paragraphs 27 and 60, element “10” corresponding to a time-of-flight sensor generating a point cloud (i.e. depth map); and
a controller coupled to the time-of-flight sensor (Fig. 1a, 1b, 2, element 30; paragraphs 27 and 68, wherein the “computing unit” (30) corresponds to a controller physically or wirelessly coupled to the TOF sensor), the controller configured to:
conducting a paragraphs 38, 71-74, wherein a search for object edges is conducted on the point cloud (i.e. depth map)),
detecting edges of an object (paragraphs 38, 71-74, wherein an object edges are detected on the point cloud (i.e. depth map))
calculating one or more high-level parameters related to the object (paragraphs 38, 47-49 and 87, wherein high-level parameters (e.g. bending radius of the edge, length/size of the edge, etc.) are calculated based on a merit function); and
repeating the paragraphs 38 and 47, wherein the process of searching for object edges is repeated corresponding to searching for cells that have not been “swept” (i.e. searched) to identify other edges (i.e. similar objects)).
As indicated by the double strike throughs above, Niklaus does not disclose expressly that the search on the depth map is a raster or spiral search, that the raster search comprising alternating between sweeping left to right and then up and down systematically, the spiral search comprising a circumferential-direction scanning, and detecting edges of an object to guide a continuation of the raster or spiral search.
Fu discloses a technique for object abstraction to distinguish between different objects in an image (Figs. 5, 6, 10, column 10, lines 9-60 and column 12, line 19 – column 13, line 8, wherein edges are distinguished between different objects in an image), the method comprising:
conducting a raster or spiral search on the image, the raster search comprising alternating between sweeping left to right and then up and down systematically, the spiral search comprising a circumferential-direction scanning (Figs. 10 and column 12, line 19 – column 13, line 8, wherein edges are searched for using both raster and spiral methods disclosed in the claim);
detecting edges of an object to guide a continuation of the raster or spiral search (Figs. 10 and column 12, line 19 – column 13, line 8, wherein the detection of an object edge guides the continuation of the search direction, using the raster and/or spiral search disclosed, to trace the object); and
repeating the raster or spiral search for cells of the image that have not been previously swept to similarly identify other objects (Figs. 10 and column 12, line 19 – column 13, line 8, wherein the search is repeated for each edge pixel not previously swept using the raster and/or spiral search).
Niklaus & Fu are combinable because they are from the same art of image processing, specifically edge detection.
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to incorporate a raster and/or spiral search for object edge detection, the raster search comprising alternating between sweeping left to right and then up and down systematically, the spiral search comprising a circumferential-direction scanning, and using detected edges of an object to guide a continuation of the raster and/or spiral search, as taught by Fu, into the process of detecting edges in a point cloud (i.e. depth map) for distinguishing being different objects as disclosed by Niklaus.
The suggestion/motivation for doing so would have been to provide simple and quick image processing techniques such as detecting edge pixels based on adjacent pixels and a local derivative (Fu, column 3, lines 40-46 and column 4, lines 1-8) .
Therefore, it would have been obvious to combine Fu with Niklaus to obtain the invention as specified in claim 28.
Regarding claim 29, the combination of Niklaus and Fu discloses the device of claim 28, wherein the one or more high-level parameters of the object comprises a center, a size, a minimum range, a median range, a maximum range, a reflectance, or a combination thereof (Niklaus, paragraphs 38, 47-49 and 87, wherein high-level parameters (e.g. length of the edge (i.e. “size”) or mean intensity (i.e. “reflectance” )) are calculated based on a merit function).
Claims 7 and 27 are rejected under 35 U.S.C. 103 as being unpatentable over US 2023/0288201 to Niklaus et al. (“Niklaus”) in view of USPN 5,615,287 to Fu et al. (“Fu”), in further view of USPN 9,681,073 to Jin et al. (“Jin”).
Regarding claim 7, the combination of Niklaus and Fu discloses the method of claim 1.
However, the combination does not disclose expressly applying different threshold values to remove veiling glare effect for each object identified.
Jin discloses a technique of compensating for veiling glare in an image by applying different threshold values to remove veiling glare effect for each object identified (column 4, lines 48-60 and column 6, line 33 – column 7, line 4, wherein threshold values are applied to, for example, a VG_ratio to determine an amount of veiling glare in an image and if needed the glare is compensated for (i.e. removed)).
Niklaus, Fu & Jin are combinable because they are from the same art of image processing.
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to incorporate the technique of applying different threshold values to remove veiling glare effect for each object identified, as taught by Jin, into the process of object abstraction disclosed by the combination of Niklaus and Fu.
The suggestion/motivation for doing so would have been to compensate for veiling glare in images (Jin, column 1, lines 39-62).
Therefore, it would have been obvious to combine Jin with Nicklaus and Fu to obtain the invention as specified in claim 7.
Regarding claim 27, the combination of Niklaus and Fu discloses the time-of-flight circuit of claim 21.
However, the combination does not disclose expressly applying different threshold values to remove veiling glare effect for each object identified.
Jin discloses a technique of compensating for veiling glare in an image by applying different threshold values to remove veiling glare effect for each object identified (column 4, lines 48-60 and column 6, line 33 – column 7, line 4, wherein threshold values are applied to, for example, a VG_ratio to determine an amount of veiling glare in an image and if needed the glare is compensated for (i.e. removed)).
Niklaus, Fu & Jin are combinable because they are from the same art of image processing.
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to incorporate the technique of applying different threshold values to remove veiling glare effect for each object identified, as taught by Jin, into the time-of-flight circuit for object abstraction disclosed by the combination of Niklaus and Fu.
The suggestion/motivation for doing so would have been to compensate for veiling glare in images (Jin, column 1, lines 39-62).
Therefore, it would have been obvious to combine Jin with Niklaus and Fu to obtain the invention as specified in claim 27.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See attached PTO-892.
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/AARON W CARTER/Primary Examiner, Art Unit 2661
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