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 .
Election/Restrictions
Applicant’s election without traverse of embodiment 1, claims 1-5, in the reply filed on 12/5/25 is acknowledged.
Claims 6-20 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected embodiment, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 12/5/25.
Applicant is reminded that upon the cancelation of claims to a non-elected invention, the inventorship must be corrected in compliance with 37 CFR 1.48(a) if one or more of the currently named inventors is no longer an inventor of at least one claim remaining in the application. A request to correct inventorship under 37 CFR 1.48(a) must be accompanied by an application data sheet in accordance with 37 CFR 1.76 that identifies each inventor by his or her legal name and by the processing fee required under 37 CFR 1.17(i).
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Drawings
The drawings are objected to because all diagrams and features in Figure 3 are required to be distinctly labeled to indicate contents or function with legends (37 C.F.R. 1.83(a), 1.84(o)) since they are necessary for understanding of the drawing. Correction is required.
Specification
Applicant is reminded of the proper language and format for an abstract of the disclosure.
The abstract should be in narrative form and generally limited to a single paragraph on a separate sheet within the range of 50 to 150 words in length. The abstract should describe the disclosure sufficiently to assist readers in deciding whether there is a need for consulting the full patent text for details.
The language should be clear and concise and should not repeat information given in the title. It should avoid using phrases which can be implied, such as, “The disclosure concerns,” “The disclosure defined by this invention,” “The disclosure describes,” etc. In addition, the form and legal phraseology often used in patent claims, such as “means” and “said,” should be avoided.
The abstract of the disclosure is objected to because of inclusion of implied and legal phraseologies such “disclosure” and “embodiments”. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-5 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Hyeon et al (KR 10-2270625).
Hyeon et al (see attached English translation), in Figs. 1, 2, and 4, discloses the same road situation detection device as specified in claim 1 of the present invention, comprising a memory 130 comprising instructions [0040]; and a processor 150 configured to, by executing the instructions, determine a roadway 10 in a captured image [0068] through region 10 distinguishing in the captured image, and determine an abnormal situation (e.g. reverse driving) regarding driving of a vehicle object 20 in the roadway in the captured image [0032].
Claim 2, wherein the processor is configured to distinguish between a driving road region 10 and a non-driving road region (e.g. Fig. 1) in the captured image, based on a pretrained region distinguishing model (e.g. AI learning), and determine that the distinguished driving road region is the roadway [0001].
Claim 3, wherein the region distinguishing model is a deep learning model [0001] that is defined to distinguish between a driving road region 10, in which a vehicle 20 travels, and a non-driving road region, in which a non-vehicle moving object (e.g. bicycle) moves, by being trained on training data based on a movement speed and a movement trajectory of an unspecified moving object (e.g. not motor vehicle) identified in a captured image, based on multiple images 210 captured under shooting conditions identical to those of the captured image [0040], and wherein from the training data, relevant data of a specific moving object that is capable of moving on both a roadway and a sidewalk are excluded [0037].
Claim 4, wherein the specific moving object is configured as a moving object 20 for which an audio waveform of a specific tire friction sound, which specifies an electric scooter (e.g. electric kickboard) and a bicycle [0037] from among unspecified moving objects identified in each of the multiple captured images 210, is detected based on tire friction sound data 200 acquired at time points when the multiple captured images are taken at a location of a device 100 configured to take the captured image.
Claim 5, wherein the abnormal situation is determined in case that a driving direction (e.g. reverse) of a vehicle object 20 recognized on the roadway in the captured image is recognized to be opposite or different from a driving direction (e.g. one-way) of the roadway, or in case that the vehicle object recognized on the roadway stops driving at situation other than a predefined normal situation [0051]-[0052].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
20260011153 discloses METHOD FOR EVALUATING AND/OR IMPROVING A TOTAL DEPTH MAP OF A MONITORING AREA AND TOTAL DEPTH MAP ARRANGEMENT FOR IMPLEMENTING THE METHOD
20260011172 discloses ANIMAL IDENTIFICATION AND FORECASTING SYSTEM AND METHOD
20260011154 discloses INCIDENT SURVEILLANCE USING UNMANNED MOBILE MACHINES
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/Y LEE/ Primary Examiner, Art Unit 2485