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 .
This Office Action is in response to Applicant’s amendment filed 07/20/2026. Claims 1 and 3-20 are currently pending in this application.
Claim Rejections - 35 USC § 101
Applicant’s amendment to claim 1 to define that the method steps are performed by a processor, and wherein the steps of claim 1 are performed in combination with the steps of previous claim 2, now canceled, overcomes the previous rejection under 35 U.S.C. 101. Claim 1, as amended, requires vehicle detection and tracking that utilizes one frame of image for tracking a vehicle in at least one subsequent frame, recording vehicle detection boxes of successive frames, and under a condition that a ratio of an overlapping area of the vehicle detection boxes of the vehicle in adjacent frames of images is greater than or equal to a preset ratio threshold, identifying the vehicle model information of the vehicle, which in combination, requires a transformation of image data to vehicle model information, wherein the vehicle model information is related to the violation determination step. The Examiner notes, however, that the amendment to include “the processor” by itself does not cure the previous deficiencies under 35 U.S.C. 101.
Applicant’s amendment to claim 11 to define a non-transitory storage medium is interpreted in light of the Applicant’s specification on Page 30 that defines a computer storage medium (or a non-transitory medium) that is separate from a communication medium (or a transitory medium). The previous rejection under 35 U.S.C. 101 is hereby withdrawn.
Claim Rejections - 35 USC § 112
Applicant’s amendment to claim 3 overcomes the previous rejection under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph. The rejection is hereby withdrawn.
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.
Claims 1, 3-7, and 10-17 are rejected under 35 U.S.C. 103 as being unpatentable over Mimeault et al. (U.S. 2014/0159925 A1).
Claim 1, Mimeault teaches:
A vehicle violation detection method, applied to a vehicle violation detection device (Mimeault, Fig. 1: 10), comprising:
acquiring, by a processor of the vehicle violation detection device (Mimeault, Fig. 1: 22, Paragraphs [0090], [0092], and [0098-0099], The control and processing unit 22 handles the synchronization, acquisition, and image processing.), a plurality of frames of images, carrying out, by the processor, vehicle detection and tracking according to the plurality of frames of images, and generating, by the processor, vehicle information of a detected vehicle, wherein the vehicle information comprises a vehicle detection box and vehicle model information (Mimeault, Figs. 27A-27D and Figs. 28A-28D, Paragraphs [0151-0152], The system utilizes the plurality of images using an object-box approach to determine the type of vehicle and appropriate size of the box to depict the type of vehicle (see Mimeault, Figs. 25A-25C, Paragraph [0150]).);
the vehicle model information corresponds to a vehicle physical size (Mimeault, Figs. 25A-25C, Paragraph [0150]);
determining, by the processor, a correspondence relationship between image coordinates in the images and absolute spatial coordinates according to a size of a vehicle detection box of the vehicle and a vehicle physical size corresponding to vehicle model information of the vehicle (Mimeault, Figs. 25A-25C, Paragraph [0150], When establishing the bounding boxes, with the sizes relative to the size of the vehicle, the system also determines the corresponding Cartesian coordinates of the vehicle(s) relative to the point of origin of the sensor (see Mimeault, Paragraph [0124] for example).), and determining, by the processor, speed information of the vehicle according to the correspondence relationship (Mimeault, Paragraph [0127], The position, speed, class, and trigger for the vehicles located in the detection zone may be used for determining speed violations (see Mimeault, Paragraph [0116]).); and
carrying out, by the processor, violation determination of the vehicle according to the speed information of the vehicle (Mimeault, Paragraph [0116]).
wherein acquiring, by the processor of the vehicle violation detection device, the plurality of frames of images, and carrying out vehicle detection and tracking according to the plurality of frames of images comprises:
acquiring, by the processor, one frame of image; under a condition that a vehicle is detected in the frame of image, tracking, by the processor, the vehicle in at least one subsequent frame of image; recording, by the processor, vehicle detection boxes of successive S frames of images of the vehicle (Mineault, Figs. 27A-27D and Figs. 28A-28D, Paragraphs [0151-0152], In the example of Figs. 27 and 28, at least four images, i.e. S frames = 4, of the same vehicle are captured sequentially.).
Mimeault does not explicitly teach:
Under a condition that a ratio of an overlapping area of vehicle detection boxes of the vehicle in adjacent frames of images of the S frames of image to an area of any vehicle detection box of the vehicle in the adjacent frames of images is greater than or equal to a preset ratio threshold, identifying, by the processor, vehicle model information of the vehicle, wherein, 0 < the preset ratio threshold < 1, and S is an integer greater than 1.
However, Figs. 27B-27D, which represent three frames, i.e. S = 3, show a box for a vehicle, wherein the box for Fig. 27B contains an overlapping portion to the box for Fig. 27C, which contains an overlapping portion to the box in Fig. 27D. Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, for the system to be capable of generating successive boxes for a vehicle wherein the ratio from one image to another is less than 1 but still greater than a preset ratio threshold (which is also less than 1 but greater than 0), i.e. successive boxes in successive images are larger but also at least partially overlap with previous boxes in previous images.
Claim 3, Mimeault teaches:
The vehicle violation detection method according to claim 1.
Mimeault does not explicitly teach:
Wherein 0.35 ≤ the preset ratio threshold ≤ 0.75.
However, Figs. 27B-27D, which represent three frames, i.e. S = 3, show a box for a vehicle, wherein the box for Fig. 27B contains an overlapping portion to the box for Fig. 27C, which contains an overlapping portion to the box in Fig. 27D. Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, for the system to be capable of generating successive boxes for a vehicle wherein the ratio from one image to another is less than 1 but still greater than a preset ratio threshold (which is also less than 0.75 but greater than 0.35), i.e. successive boxes in successive images are larger but also at least partially overlap with previous boxes in previous images.
Claim 4, Mimeault further teaches:
The vehicle violation detection method according to claim 1, wherein determining the speed information of the vehicle according to the correspondence relationship comprises:
determining absolute spatial coordinates corresponding to same positions in vehicle detection boxes of two frames of images according to the correspondence relationship (Mimeault, Figs. 25A-25C, Paragraph [0150], The system determines the Cartesian coordinates of the detected vehicle(s).), determining a displacement distance between the same positions in the vehicle detection boxes of the two frames of images according to the absolute spatial coordinates corresponding to the same positions in the vehicle detection boxes of the two frames of images (Mimeault, Figs. 27A-27D and Figs. 28A-28D, Paragraphs [0151-0152], As the vehicle(s) drive past the system, the relative distance within the Cartesian coordinate system may be determined for each vehicle.), and determining a first speed of the vehicle according to the displacement distance and a time interval between the two frames of images (Mimeault, Paragraph [0118], The speed of each vehicle is determined by the amount of time it takes to displace the vehicle between the two points (in images).);
taking the first speed as the speed information of the vehicle (Mimeault, Paragraph [0118], The calculated speed of the vehicle is the speed information of the vehicle.); or, acquiring a plurality of first speeds according to images of different frames, and taking an average value of the plurality of first speeds as the speed information of the vehicle.
Claim 5, Mimeault further teaches:
The vehicle violation detection method according to claim 4, wherein the two frames of images are two adjacent frames of images (Mimeault, Figs. 27A-27D and Figs. 28A-28D, Paragraphs [0151-0152]);
acquiring the plurality of first speeds according to images of different frames comprises:
acquiring the plurality of first speeds according to images of every two adjacent frames in a successive plurality of frames of images (Mimeault, Paragraph [0127], Each frame may have an associated position, speed, class and trigger for each vehicle in the detection zone.).
Claim 6, Mimeault further teaches:
The vehicle violation detection method according to claim 1, wherein carrying out the violation determination of the vehicle according to the speed information of the vehicle comprises at least one of the following:
determining illegal parking of the vehicle under a condition that the speed information of the vehicle is zero, the vehicle is located in an illegal parking lane, and a time for the vehicle to stay in the illegal parking lane is greater than a preset first alarm time threshold;
determining vehicle accident under a condition that the speed information of the vehicle is zero, the vehicle is located in a non-illegal parking lane, a time for the vehicle to stay in the non-illegal parking lane is longer than a preset third alarm time threshold, and a pedestrian or a preset warning sign is detected in a preset periphery range of the vehicle detection box;
determining illegal parking of the vehicle under a condition that the speed information of the vehicle is zero, the vehicle is located in a non-illegal parking lane, a time for the vehicle to stay in the non-illegal parking lane is longer than the preset third alarm time threshold, and a pedestrian or a preset warning sign is not detected in the preset periphery range of the vehicle detection box;
determining illegal wrong way of the vehicle under a condition that the speed information of the vehicle is non-zero, a driving direction of the vehicle is inconsistent with a driving direction of a lane where the vehicle is located, and a time for the vehicle to drive on wrong way is longer than a preset second alarm time threshold;
determining illegal low-speed of the vehicle under a condition that the speed information of the vehicle is less than a preset low-speed threshold, a driving direction of the vehicle is consistent with a driving direction of a lane where the vehicle is located, and a time for the speed information of the vehicle less than the preset low-speed threshold is longer than a preset fourth alarm time; and
determining illegal speeding of the vehicle under a condition that the speed information of the vehicle is greater than a preset speeding threshold, a driving direction of the vehicle is consistent with a driving direction of a lane where the vehicle is located, and a time for the speed information of the vehicle greater than the preset speeding threshold is greater than a preset fifth alarm time (Mimeault, Paragraph [0116], Speed enforcement is based on a speed limit, i.e. a preset speeding threshold, which is stored in the detector (see Mimeault, Paragraph [0017]). Thus, the time at which a speed and identity of the vehicle at the speed is detected is a time for the speed information.).
Claim 7, Mimeault further teaches:
The vehicle violation detection method according to claim 1, wherein the vehicle information further comprises:
license plate information (Mimeault, Paragraph [0112]);
the method further comprises: after the violation determination of the vehicle is carried out according to the speed information of the vehicle and that the vehicle has violation is determined, (Mimeault, Paragraph [0116], An owner of the vehicle may be identified using information from the license plate during a speed enforcement situation. The driver and/or owner of the vehicle is issued a traffic infraction ticket.).
Mimeault does not explicitly teach:
Determining a terminal equipment associated with the vehicle according to the license plate information and sending violation behavior information of the vehicle to the terminal equipment associated with the vehicle.
However, it would have been obvious to one of ordinary skill in the art, at the time of filing, for the system to be capable of determining a terminal equipment, e.g. a house address or a computer having access to email, to issue the traffic infraction ticket. Such a modification would ensure that the system is capable of performing its intended function, i.e. issuing the traffic infraction ticket to drivers and/or owners based on detected driving behavior, and would therefore yield predictable results.
Claim 10, Mimeault further teaches:
A vehicle violation detection device (Mimeault, Fig. 1), comprising a processor and a memory (Mimeault, Paragraph [0096]), wherein the processor implements the acts of the vehicle violation detection method according to claim 1 (Mimeault, Paragraph [0096], An embodiment of the control and processing unit 22 includes a personal computer (PC) board, wherein the control and processing unit 22 is configured to operate numerous functions (see Mimeault, Paragraph [0098]).).
Mimeault does not explicitly teach:
The memory storing a computer program runnable on the processor, wherein the processor executes the program.
However, it would have been obvious to one of ordinary skill in the art, at the time of filing, for the control and processing unit 22 to include a computer program runnable on the processor, e.g. when operating as a microcontroller or a PC board. Such a modification would not change the principal operation of the system, as a whole, and would yield predictable results.
Claim 11, Mimeault further teaches:
A computer-readable non-transitory storage medium (Mimeault, Paragraph [0096]) and the vehicle violation detection method according to claim 1 (Mimeault, Fig. 1).
Mimeault does not explicitly teach:
The computer-readable non-transitory storage medium storing program instructions under a condition that the program instructions are executed, the program instructions can perform the vehicle violation detection method.
However, it would have been obvious to one of ordinary skill in the art, at the time of filing, for the control and processing unit 22 to include program instructions executable by the processor, e.g. when operating as a microcontroller or a PC board. Such a modification would not change the principal operation of the system, as a whole, and would yield predictable results.
Claim 12, Mimeault further teaches:
A vehicle violation detection system (Mimeault, Fig. 1), comprising: a video acquiring device (Mimeault, Paragraph [0090], The system utilizes a combination of optical receivers and cameras.), and the vehicle violation detection device according to claim 10, wherein the video acquiring device is configured to acquire an image of a preset monitoring region and send the image to the vehicle violation detection device (Mimeault, Paragraph [0090], Video data is transmitted for some applications to help identify vehicles.).
Claim 13, Mimeault teaches:
A vehicle violation detection device (Mimeault, Fig. 1), comprising:
a processor (Mimeault, Fig. 1: 22, Paragraphs [0098-0099], The control and processing unit 22 has numerous functions, including detecting the presence of vehicles by controlling a plurality of devices of the system, e.g. emitters and illuminators (see Mimeault, Paragraphs [0096-0097]).), wherein:
the processor is configured to acquire a plurality of frames of images, carry out vehicle detection and tracking according to the plurality of frames of images, and generate vehicle information of a detected vehicle, wherein the vehicle information comprises a vehicle detection box and vehicle model information (Mimeault, Figs. 27A-27D and Figs. 28A-28D, Paragraphs [0151-0152], The system utilizes the plurality of images using an object-box approach to determine the type of vehicle and appropriate size of the box to depict the type of vehicle (see Mimeault, Figs. 25A-25C, Paragraph [0150]).), and the vehicle model information corresponds to a vehicle physical size (Mimeault, Figs. 25A-25C, Paragraph [0150]); and
utilizing the vehicle information, the processor is further configured to determine a correspondence relationship between image coordinates in the images and absolute spatial coordinates according to a size of a vehicle detection box of the vehicle and a vehicle physical size corresponding to vehicle model information of the vehicle (Mimeault, Figs. 25A-25C, Paragraph [0150], When establishing the bounding boxes, with the sizes relative to the size of the vehicle, the system also determines the corresponding Cartesian coordinates of the vehicle(s) relative to the point of origin of the sensor (see Mimeault, Paragraph [0124] for example).), and determine speed information of the vehicle according to the correspondence relationship (Mimeault, Paragraph [0127], The position, speed, class, and trigger for the vehicles located in the detection zone may be used for determining speed violations (see Mimeault, Paragraph [0116]).); and
carry out violation determination of the vehicle according to the speed information of the vehicle (Mimeault, Paragraph [0116]);
wherein the processor is configured to acquire the plurality of frames of images, and carry out vehicle detection and tracking according to the plurality of frames of images by: acquiring one frame of image; under a condition that a vehicle is detected in the frame of image, tracking the vehicle in at least one subsequent frame of image; recording vehicle detection boxes of successive S frames of images of the vehicle (Mineault, Figs. 27A-27D and Figs. 28A-28D, Paragraphs [0151-0152], In the example of Figs. 27 and 28, at least four images, i.e. S frames = 4, of the same vehicle are captured sequentially.).
Mimeault does not explicitly teach:
A vehicle information identification module and a violation behavior detection module processor;
and under a condition that a ratio of an overlapping area of vehicle detection boxes of the vehicle in adjacent frames of images of the S frames of image to an area of any vehicle detection box of the vehicle in the adjacent flames of images is greater than or equal to a preset ratio threshold, identifying vehicle model information of the vehicle, wherein, 0 < the preset ratio threshold < l, and S is an integer greater than 1.
As per a vehicle information identification module and a violation behavior detection module processor, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify the control and processing unit 22 to include separate units and processors for different purposes, i.e. a vehicle information identification module having a processor and a violation behavior detection module having a processor, as a matter of engineering choice. Such a modification would not change the principal operation of the system, as a whole, and would yield predictable results.
As per under a condition that a ratio of an overlapping area of vehicle detection boxes of the vehicle in adjacent frames of images of the S frames of image to an area of any vehicle detection box of the vehicle in the adjacent flames of images is greater than or equal to a preset ratio threshold, identifying vehicle model information of the vehicle, wherein, 0 < the preset ratio threshold < l, and S is an integer greater than 1, Figs. 27B-27D, which represent three frames, i.e. S = 3, show a box for a vehicle, wherein the box for Fig. 27B contains an overlapping portion to the box for Fig. 27C, which contains an overlapping portion to the box in Fig. 27D. Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, for the system to be capable of generating successive boxes for a vehicle wherein the ratio from one image to another is less than 1 but still greater than a preset ratio threshold (which is also less than 1 but greater than 0), i.e. successive boxes in successive images are larger but also at least partially overlap with previous boxes in previous images.
Claim 14, Mimeault further teaches:
The vehicle violation detection method according to claim 1, wherein before the violation determination of the vehicle is carried out based on the speed information of the vehicle, the method further comprises: determining lane type information, lane speed threshold information, and lane driving direction (Mimeault, Paragraph [0117], The detector stores speed limit data (which can be different for each lane), i.e. lane speed threshold information, in order to determine whether the vehicle’s speed is in violation with the speed limit.).
Claim 15, Mimeault further teaches:
The vehicle violation detection method according to claim 6.
Mimeault does not explicitly teach:
Wherein an area of the preset periphery range and an area of the vehicle detection box are 2 to 4 times the area of the vehicle detection box.
However, it would have been obvious to one of ordinary skill in the art for the area coverage of the detector to be within the range of 2 to 4 times of the area of the vehicle bounding box, as a matter of engineering choice. Such a modification would enable the system to function for its intended function and would yield predictable results. See MPEP 2144.04. The Examiner additionally notes that claim 15 depends on claim 6, wherein the limitations of claim 6 are presented in the alternative form, i.e. “at least one of the following”. Therefore, the limitations regarding the preset periphery range are not required based on the alternative form in claim 6.
Claim 16, Mimeault further teaches:
The vehicle violation detection method according to claim 4, wherein the two frames of images are two non-adjacent frames of images (Mimeault, Figs. 27A-27D and Figs. 28A-28D, Paragraphs [0151-0152], Examples of two non-adjacent frames include 27A and 27C, or 27B and 27D.).
Claim 17, Mimeault further teaches:
The vehicle violation detection method according to claim 1, wherein the vehicle information further comprises: an average driving speed of a vehicle, a maximum driving speed of a vehicle, a minimum driving speed of a vehicle, a vehicle trajectory (Mimeault, Paragraph [0118], One example speed is an average speed of the vehicle.).
Claims 8-9 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Mimeault et al. (U.S. 2014/0159925 A1) in view of Wang (U.S. 2016/0232785 A1).
Claim 8, Mimeault further teaches:
The vehicle violation detection method according to claim 7, wherein the method further comprises: storing vehicle information, and violation behavior information generated after the violation determination of the vehicle is carried out (Mimeault, Paragraphs [0116-0117], The detector can store data relating to violations.).
Mimeault does not specifically teach:
Performing statistics based on the vehicle information and the violation behavior information to generate statistical information, and sending statistical information related to the vehicle to the terminal equipment associated with the vehicle, wherein the statistical information related to the vehicle comprises at least one of the following: statistical information obtained by performing statistics based on violation behavior information of the vehicle, and statistical information obtained by performing statistics based on violation behavior information of a vehicle model to which the vehicle belongs.
Wang teaches:
Performing statistics based on the vehicle information and the violation behavior information to generate statistical information (Wang, Paragraph [0079], Analyses may be performed on the database for statistical patterns regarding traffic violations that used by the users.), and sending statistical information related to the vehicle to the terminal equipment associated with the vehicle, wherein the statistical information related to the vehicle comprises at least one of the following: statistical information obtained by performing statistics based on violation behavior information of the vehicle, and statistical information obtained by performing statistics based on violation behavior information of a vehicle model to which the vehicle belongs (Wang, Paragraphs [0085-0086], Statistical analysis may be performed on driving behaviors within a given area, and the results of the analysis may be transmitted to users as notifications.).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify the system in Mimeault by integrating the teaching of statistical analysis as taught by Wang.
The motivation would be to reduce or prevent traffic violations through education and awareness (see Wang, Paragraph [0079]).
Claim 9, Mimeault in view of Wang further teaches:
The vehicle violation detection method according to claim 8, wherein the violation behavior information comprises a road section where a violation behavior occurred, and the statistical information comprises at least one of the following: frequencies of different violation behaviors of a same vehicle, frequencies of different violation behaviors of a same vehicle model, and frequencies of violation behaviors of a same vehicle model on different road sections (Wang, Paragraphs [0085-0086], The statistical analysis is performed on a specific roadway, e.g. a roadway that may be unfamiliar to a user who has to drive across state/county lines. It would have been obvious to one of ordinary skill in the art, at the time of the invention, for the database to store data of drivers operating similar vehicles in order to better serve the user’s request.).
Claim 20, Mimeault further teaches:
The vehicle violation detection method according to claim 1.
Mimeault does not specifically teach:
Further comprising: periodically performing statistics of violation behaviors at a preset period.
Wang teaches:
Further comprising: periodically performing statistics of violation behaviors at a preset period (Wang, Paragraph [0079], Analysis may be performed on the database for statistical patterns regarding traffic violations that used by the users. It would have been obvious to one of ordinary skill in the art, at the time of filing, for the analysis to be performed periodically in order to utilize up-to-date data to determine the statistical patterns.).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify the system in Mimeault by integrating the teaching of statistical analysis as taught by Wang.
The motivation would be to reduce or prevent traffic violations through education and awareness (see Wang, Paragraph [0079]).
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Mimeault et al. (U.S. 2014/0159925 A1) in view of Ratti (U.S. 2018/0211117 A1).
Claim 18, Mimeault further teaches:
The vehicle violation detection method according to claim 1, further comprising: performing license plate identification (Mimeault, Paragraph [0112]).
Mimeault does not explicitly teach:
According to a license plate identification neural network model.
Ratti teaches:
According to a license plate identification neural network model (Ratti, Paragraph [0088]).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to substitute the license plate recognition in Mimeault with the neural network model for the license plate information, as taught by Ratti. The result of such a substitution would have been predictable and would maintain the system’s ability to recognize license plate information.
Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over Mimeault et al. (U.S. 2014/0159925 A1) in view of Tang et al. (U.S. 10,325,315 B1).
Claim 19, Mimeault further teaches:
The vehicle violation detection method according to claim 1, further comprising: performing vehicle model identification (Mimeault, Paragraph [0090], The system utilizes images to identify vehicles, wherein vehicles includes different types of vehicles (see Mimeault, Paragraph [0043]).).
Mimeault does not explicitly teach:
Further comprising: performing vehicle model identification according to a vehicle model identification neural network model.
Tang teaches:
Further comprising: performing vehicle model identification according to a vehicle model identification neural network model (Tang, Paragraph (0136), The second convolutional neural network is used to determine a vehicle make and model.).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to substitute the vehicle identification in Mimeault with the second convolutional neural network for the make and model of the vehicle, as taught by Tang. The result of such a substitution would have been predictable and would maintain the system’s ability to recognize vehicles.
Response to Arguments
Applicant's arguments filed 07/20/2026 have been fully considered but they are not persuasive.
In response to the Applicant’s argument on Pages 11-14 that the Mimeault reference fails to teach the distinguishing feature of the Applicant’s claims, as amended, the Examiner respectfully disagrees. The limitation, i.e. the “ratio of an overlapping area of vehicle detection boxes” is claimed in claims 1 and 13, but the ratio is claimed as “under a condition”. The broadest reasonable interpretation of the limitation of the “ratio” in view of “under a condition” is, with respect to the Mimeault reference, if successive boxes in adjacent images have bounding boxes that overlap in size, then the bounding boxes are under a condition of having a ratio. It appears that the Applicant intends for the method and device to use successive S frames of images to retrieve detection boxes in each of the frames, overlay the detection boxes, and subsequently calculating a ratio based on a comparison of the detection boxes. The claims, as currently amended, do not inherently or explicitly define the invention to perform these steps, but only claim the “condition” of the ratios. Therefore, “under a condition” is interpretable as only requiring the relationship between detection boxes of successive frames to have a ratio. Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). As per the ratio between successive frames, as disclosed in the rejection above and further clarified, rectangle 701 of Fig. 27B is smaller than and overlaps with the rectangle 701 of Fig. 27C, and rectangle 701 of Fig. 27C is smaller than and overlaps with rectangle 701 in Fig. 27D. Therefore, one of ordinary skill in the art would recognize that the ratio between the overlapping portion of rectangles 701 in Fig. 27B and 27C to the box in Fig. 27C and the ratio between the overlapping portion of rectangles 701 in Fig. 27C and 27D to the box in Fig. 27D are less than 1 because each former box is smaller than the latter box. Therefore, it is within the teachings of Mimeault for the ratios to be greater than a preset ratio threshold, because the Applicant’s claimed preset ratio threshold is only limited to not being 0, e.g. no overlapping portions of the boxes, or 1, e.g. for the detection boxes to be the same, one of ordinary skill in the art would be motivated to set the preset ratio threshold to any value less than 1 but greater than 0.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES J YANG whose telephone number is (571)270-5170. The examiner can normally be reached 9:30am-6:00p M-F.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, BRIAN ZIMMERMAN can be reached at (571) 272-3059. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JAMES J YANG/Primary Examiner, Art Unit 2686
