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 .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefore, subject to the conditions and requirements of this title.
Claims 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because regarding claim 17, the claim recites the computer program product, the computer program product comprising a computer readable storage medium storing program instruction, examiner broadest reasonable interpretation of the specification describing computer readable storage medium, teaches a signal. The specification paragraph 0057 describes storage mediums as semiconductor or solid-state memory, magnetic tape, a removable computer diskette, a random-access memory (RAM), a read-only memory (ROM), a rigid magnetic disk and an optical disk, etc. Using term etc. leaves a possibility it can be a signal. Examiner suggest amending the claim to include non-transitory. Claim 18-20 depend on claim 17. Therefore, they are also rejected.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 7-9, 15-17 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Schulter et al (12,670,719).
Regarding method claim 1, system claim 9 and computer program claim 17 Schulter discloses,
detecting one or more objects in an image (note fig. 1, block 110 and 112, col. 3 lines 13-14, object detection data and image);
generating one or more captions for the image (note fig. 1, block 120, images 120 and caption and col. 3 lines 21-23, image caption 120);
matching one or more predicted categories of the one or more objects detected in the image and the one or more captions to identify, from the one or more predicted categories, a category of a novel object in the image (note col. 3 lines 41-49 and col. 6 lines 8-20, open vocabulary, object identified potentially dangerous situation);
generating an image feature and a text description feature using a description of the novel object (note col. 4 lines 47-52 and col. 5 lines 62- col. 6 lines 7, semantics of open vocabulary provide insights of the potentially dangerous situation);
selecting a relevant image using a similarity score between the image feature and the text description feature (note col. 4 lines 10-25; and
updating a model using the relevant image and associated description of the novel object (note col. 3 lines 61-64, with respected to neural network, parameters updated during training).
Regarding method claims 7 and system claim 15 Schulter discloses,
Wherein updating the model includes self-training (note fig. 8 block 1007).
Regarding method claim 8, system claim 16 and computer program claim 20 Schulter discloses,
Wherein the method is implemented by an autonomous driving vehicle (note col. 5 lines 13-21 and 28-30, use this feature in autonomous vehicles).
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 2-6, 10-14 and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Schulter et al (12,670,719) in view of Yu et al (12,387,340).
Regarding method claim 2 and system claim 10 Schulter discloses,
Updating a model, Schulter does not clearly disclose iterating to refine the model.
Yu discloses iterating to refine the model (note fig. 2b block 225 and col. 5 lines 20-25 iterative masking).
Schulter and Yu are combinable because they are from the same field of endeavor. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claim invention to include
iterating to refine the model in the system of Schulter as evidence by Yu. The suggestion/motivation for doing so provides improve performance of novel samples (note col. 16 lines 32-39). It would have been obvious to combine Yu with Schulter to obtain the invention as specified by claims 2 and 10.
Regarding method claim 3, system claim 11 and computer program claim 18 Schulter discloses,
Updating the model includes running an object proposal network to obtain bounding boxes for each object in the image (note Schulter col. 3 lines 13-20 and 40-45, object instance is described with a bounding box); and Schulter does not clearly disclose pseudo-labeling each object in the bounding boxes. Yu discloses pseudo-labeling each object (note col. 3 lines 30-35, pseudo labeling described). Schulter and Yu are combinable because they are from the same field of endeavor. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claim invention to include pseudo labeling each object in the system of Schulter as evidence by Yu. The suggestion/motivation for doing so provides improve performance of novel samples (note col. 16 lines 32-39). It would have been obvious to combine Yu with Schulter to obtain the invention as specified by claims 3, 11 and 18.
Regarding method claim 4 and system claim 12 Schulter discloses,
Wherein updating the model includes running an object proposal network to obtain bounding boxes for each object in the image (note Schulter col. 3 lines 13-20 and 40-45, object instance is described with a bounding box); and Schulter does not clearly disclose employing the pseudo-labeling to increase confidence in identification of the novel objects based on context of all pseudo-labeled objects.
Yu discloses employing the pseudo-labeling to increase confidence in identification of the novel objects based on context of all pseudo-labeled objects (note col. 16 lines 22-31). Schulter and Yu are combinable because they are from the same field of endeavor. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claim invention to include employing the pseudo-labeling to increase confidence in identification of the novel objects based on context of all pseudo-labeled objects in the system of Schulter as evidence by Yu. The suggestion/motivation for doing so provides improve performance of novel samples (note col. 16 lines 32-39). It would have been obvious to combine Yu with Schulter to obtain the invention as specified by claims 4 and 12.
Regarding method claim 5 and system claim 13, Schulter discloses,
Generating one or more captions and generating the image feature and the text description features includes using a description of the novel object. Schulter does not clearly disclose generating using a visual language model (VLM) and generating the image feature and the text description features from the VLM. Vu discloses generating the one or more captions includes generating one or more captions for the image using a visual language model (VLM) and generating the image feature and the text description features includes using a description of the novel object from the VLM (note fig. 2b block 220, VLM and col. 4 lines 40-50, image encoder and text encoder, cites captions generated and VLM). Schulter and Yu are combinable because they are from the same field of endeavor. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claim invention to include generating the one or more captions includes generating one or more captions for the image using a visual language model (VLM) and generating the image feature and the text description features includes using a description of the novel object from the VLM in the system of Schulter as evidence by Yu. The suggestion/motivation for doing so provides improve performance of novel samples (note col. 16 lines 32-39). It would have been obvious to combine Yu with Schulter to obtain the invention as specified by claims 5 and 13.
Regarding method claim 6, system claim 14 and computer program claim 19 Schulter discloses,
Generating one or more captions and generating the image feature and the text description features includes using a description of the novel object. Schulter does not clearly disclose generating the image feature and the text description feature includes reducing the number of images by identifying images in a visual language model (VLM) that include potential novel objects. Vu discloses
generating the image feature and the text description feature includes reducing a number of images by identifying images in a visual language model (VLM) that include potential novel objects (note fig. 2b block 220, VLM and col. 4 lines 40-55, image encoder and text encoder, cites captions generated and VLM). Schulter and Yu are combinable because they are from the same field of endeavor. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claim invention to include generating the image feature and the text description feature includes reducing a number of images by identifying images in a visual language model (VLM) that include potential novel objects in the system of Schulter as evidence by Yu. The suggestion/motivation for doing so provides improve performance of novel samples (note col. 16 lines 32-39). It would have been obvious to combine Yu with Schulter to obtain the invention as specified by claims 6, 14 and 19
Related Prior Art
Willmott et al (12,462,552) generating one or more captions for the image (note col. 14 lines 50-60, text prompt).
Iyer et al (12,626,069) detecting one or more objects in an image (note fig. 5, block 520).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GREGORY M DESIRE whose telephone number is (571)272-7449. The examiner can normally be reached Monday-Friday 6:30am-3:00pm.
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G.D.
September 2, 2026
/GREGORY M DESIRE/Primary Examiner, Art Unit 2676
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