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 .
Claim Rejections - 35 USC § 112
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 2, 4 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.
Claim 2 recites the limitation "the procedure" in line 5. There is insufficient antecedent basis for this limitation in the claim.
Claim 4 recites the limitation “a character string immediately following a character string” in lines 2-3. It is unclear to the Examiner whether the two character strings are the same or different from each other.
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 therefor, subject to the conditions and requirements of this title.
Claim 13 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. an abstract idea) without significantly more. Using the subject matter eligibility analysis, for steps 1 and 2A, Prong 1, the claim(s) recite(s) a process but is directed to an abstract idea, specifically the mental process and method of organizing human activity of observing a task and comparing it to a set of rules. The claim recites the steps of “from an image captured…detecting the target object and a change in a state of the target object” and “correlating information about the detected change…with information about a pre-created procedure of the task”. These limitations describe the fundamental concepts of collecting information and comparing data. These are concepts that can practically be performed in the human mind or with pen and paper, such as a human supervisor watching a worker and checking off steps on a clipboard. For step 2A, Prong 2, the claim does not include additional elements that integrate the abstract idea into a practical application. The claim broadly recites capturing an image, detecting an object, and correlating the data. The claim ends at the data correlation step and does not recite what is done with the correlated information. There is no recitation of a physical transformation, no control of a downstream device, and no specific improvement to computer functionality. Gathering image data and correlating it without a subsequent technological application is merely utilizing a computer as a tool to perform an abstract idea. Therefore, the claim is not integrated into a practical application. For step 2B, the claim must be evaluated to determine if it includes additional elements that amount to significantly more than the abstract idea itself. Considered both individually and in combination, the claim elements do not add an inventive concept. The claim relies on generic, high-level components implicitly required to perform the steps, such as a generic camera to capture the “image” and a generic processor to perform the “detecting” and “correlating”. Utilizing generic hardware to capture images and process data are well understood, routine, and conventional activities in the field of computer vision and data processing. The claim lacks specific, unconventional hardware or specialized algorithmic steps that would elevate the abstract idea into an invention that amounts to significantly more than the abstract idea itself.
Claim Rejections - 35 USC § 102
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.
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.
Claim(s) 1, 2, 12, 13 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Li et al. (U.S. Patent Application 20230333523).
In regards to claim 1, Li teaches an information processing system [e.g. system, 0007] comprising:
one or more processors [e.g. computer-based processor, 0074] configured to:
from an image captured of a target object of a task and a worker performing the task [e.g. from video data of a machine and a worker performing worker actions, 0074, 0091, 0117], detect the target object and a change in a state of the target object [Fig. 1; e.g. System operates to detect and analyze a machine operation which can include one or more of worker, machine and material. System includes a first sensor, such as sensor, configured to detect a state of a first object of machine operation. Also, the sensors and sensor data are used to detect state transitions of one or more objects, 0060, 0066, 0070]; and
correlate information about the detected change in the state of the target object with information about a pre-created procedure of the task [e.g. The trained dataset may be generated for the machine operation by mapping sensed data to standard operating procedure of at least one machine component. The sensed data includes state transitions of the one or more objects. The standard operating procedure of a machine summarizes and defines the steps a worker needs to follow and the reciprocal responses from the machine or its components for the purpose of production, 0078, 0092, 0105, also see 0060].
In regards to claim 2, Li teaches the information processing system according to claim 1, wherein: the one or more processors are configured to correlate a timing of the change in the state of the target object, which is identified from the information about the change in the state of the target object, with a timing of the task, which is identified from the information about the procedure of the task [e.g. The system identifies a time interval between a state transition for the first object and a state transition for the second object. Using a standard operating procedure, sensor data may be correlated to machine actions occurring a known time intervals, and data corresponding to the time intervals may be associated with one or more actions of the machine operation. In other words, the time interval between state transitions of objects and the time interval between cause and effect of interactions are used to build a causality model, 0031, 0070-0071, 0084, 0088, 0097].
In regards to claim 12, the claim recites similar limitations as claim 1, but in the form of a non-transitory computer readable medium storing a program causing a computer to execute the steps of claim 1. Furthermore, Li teaches a non-transitory computer readable medium [e.g. memory, 0066] storing a program [e.g. one or more executable instructions, 0074] causing a computer [e.g. auxiliary advising system, 0074] to execute the steps of claim 1. Therefore, the same rationale as claim 1 is applied.
In regards to claim 13, the claim recites similar limitations as claim 1, but in method form. Therefore, the same rationale as claim 1 is applied.
Claim Rejections - 35 USC § 103
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.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 3, 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (U.S. Patent Application 20230333523) as applied to claim 2 above, and further in view of Shen et al. (Learning to Segment Actions from Visual and Language Instructions via Differentiable Weak Sequence Alignment).
In regards to claim 3, Li does not explicitly teach the information processing system according to claim 2, wherein: the one or more processors are configured to identify the timing of the task based on text data indicating content of the task, which is included in the information about the procedure of the task.
However, Shen teaches the information processing system according to claim 2, wherein: the one or more processors are configured to identify the timing of the task [Fig. 2; e.g. linguistic time-stamp for each key-step (actions required to accomplish a task), see sections titled “Introduction” and “Soft Ordered Prototype Learning” on pages 10156, 10159] based on text data indicating content of the task [Fig. 2; e.g. based on the extracted verb phrases corresponding to each key-step, see Table 1 on page 10158, see sections titled “Introduction”, “Soft Ordered Prototype Learning”, and “Narration Processing” on pages 10156, 10158-10159], which is included in the information about the procedure of the task [e.g. subtitles corresponding to the narration of the instructional video, see sections titled “Introduction” and “Narration Processing”, on pages 10156, 10158].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified Li’s system with the features of identifying the timing of the task based on text data indicating content of the task, which is included in the information about the procedure of the task in the same conventional manner as taught by Shen because Shen provides a method to improve the alignment between the images in the video and the text data indicating content of the task [see section titled “Abstract” on page 10156].
In regards to claim 4, Li does not explicitly teach the information processing system according to claim 3, wherein: the one or more processors are configured to identify the timing of the task based on a character string immediately following a character string indicating the target object, which are included in the text data.
However, Shen teaches the information processing system according to claim 3, wherein: the one or more processors are configured to identify the timing of the task [Fig. 2; e.g. linguistic time-stamp for each key-step (actions required to accomplish a task), see sections titled “Introduction” and “Soft Ordered Prototype Learning” on pages 10156, 10159] based on a character string [e.g. verb in the verb phrase, see Table 1 on page 10158, see sections titled “Introduction”, “Soft Ordered Prototype Learning”, and “Narration Processing” on pages 10156, 10158-10159] immediately following a character string indicating the target object [e.g. noun in the verb phrase, see Table 1 on page 10158, see sections titled “Introduction”, “Soft Ordered Prototype Learning”, and “Narration Processing” on pages 10156, 10158-10159], which are included in the text data.
Therefore, it would have been obvious to one of ordinary skill in the art to have modified Li’s system with the features of identifying the timing of the task based on a character string immediately following a character string indicating the target object, which are included in the text data in the same conventional manner as taught by Shen because Shen provides a method to improve the alignment between the images in the video and the text data indicating content of the task [see section titled “Abstract” on page 10156].
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (U.S. Patent Application 20230333523) as applied to claim 2 above, and further in view of Soucek et al. (Look for the Change: Learning Object States and State-Modifying Actions from Untrimmed Web Videos).
In regards to claim 8, Li does not explicitly teach the information processing system according to claim 1, wherein: the one or more processors are configured to detect a change in the state of the target object based on a chronological order of the state of the target object, which is included in each of a plurality of the images.
However, Soucek teaches the information processing system according to claim 1, wherein: the one or more processors are configured to detect a change in the state of the target object [e.g. temporally localize object states (e.g. “empty” and “full” cup) together with the corresponding state-modifying actions (“pouring coffee”), see section titled “Abstract” in page 1] based on a chronological order of the state of the target object, which is included in each of a plurality of the images [Fig. 1; e.g. based on the object states (i.e. initial state, state-modifying action, end state) ordered by its corresponding timestamps, which is included in each of the video frames, see section titled “Introduction” in pages 1-2].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified Li’s system with the features of
detecting a change in the state of the target object based on a chronological order of the state of the target object, which is included in each of a plurality of the images
in the same conventional manner as taught by Soucek because Soucek provides a method for learning object states and state-changing actions from noisy untrimmed videos from the web [see section titled “Conclusion” in page 8].
Allowable Subject Matter
Claims 5-7, 9-11 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
In regards to claim 5, the prior art of record fails to teach or suggest the information processing system according to claim 2, wherein: the one or more processors are configured to perform control to display the information about the procedure of the task on the image based on correlation between the timing of the change in the state of the target object and the timing of the task.
In regards to claim 6, the prior art of record fails to teach or suggest the information processing system according to claim 1, wherein: the one or more processors are configured to, based on correlation between the timing of the change in the state of the target object, which is identified from the information about the change in the state of the target object detected when capturing the image, and the timing of the task, which is identified from the information about the procedure of the task, perform control to display information for assisting capturing the image on a display of an information processing apparatus that is capturing the image.
In regards to claim 7, the claim depends on claim 6. Therefore, claim 7 is allowable for at least the same reason as claim 6 if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
In regards to claim 9, the prior art of record fails to teach or suggest the information processing system according to claim 8, wherein: the one or more processors are configured to, in a case where a change in the state of the target object is detected, treat a plurality of changes in the state that are detected until a change in the state of the target object is no longer detected or until the target object itself is no longer detected as a series of changes in the state of the target object.
In regards to claim 10, the prior art of record fails to teach or suggest the information processing system according to claim 1, wherein: the one or more processors are configured to determine validity of detection of target objects and changes in a state of the target objects based on a result of comparing an order of changes in the state of the target objects, which is identified from information about the changes in the state of the target objects, with an order of appearance of the target objects included in the content of the task, which is identified from the information about the procedure of the task.
In regards to claim 11, the claim depends on claim 10. Therefore, claim 11 is allowable for at least the same reason as claim 10 if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANDREW SHIN whose telephone number is (571)270-5764. The examiner can normally be reached Monday - Friday from 11:00AM to 7:00PM EST.
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/ANDREW SHIN/Examiner, Art Unit 2612
/Said Broome/Supervisory Patent Examiner, Art Unit 2612
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