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 amendment/remarks filed 06/25/2026. Claims 1, 3-4, 12, 14-15, and 20 have been amended. Claims 2 and 13 have been cancelled and claims 21-22 have been newly added. Accordingly, claims 1, 3-12, and 14-22 are pending.
Response to Arguments
Applicant’s arguments, see pages 7-8 filed 06/25/2026, with respect to the 35 U.S.C. 101 rejection have been fully considered and are persuasive. The 35 U.S.C. 101 rejection of claims 1-20 has been withdrawn, since it is now positively recited that the autonomous vehicle is controlled based on the result of the third object recognition (Further see Para. 0050-0052 of the specifications filed 11/20/2024), which includes autonomous vehicle maneuver operations and maintaining a distance from an object, which are positively recited control of the autonomous vehicle.
Applicant’s arguments, see pages 9-10 filed 06/25/2026, with respect to the 35 U.S.C. 102 have been fully considered and are persuasive, since the newly added and amended limitations are not fully disclosed in the primary reference. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Shen et al. US20200175326A1, Levy et al. US20240193805A1, and Yu et al. US20210179145A1 (henceforth Yu). See the new 35 U.S.C. 103 rejection below.
Claim Objections
Claim 21 is objected to because of the following informalities:
Claim 21 recites “a average vehicle speed” but should recite “an average vehicle speed”.
Appropriate correction is required.
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, 6, 12, 14, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Shen et al. US20200175326A1 (henceforth Shen) in view of Levy et al. US20240193805A1 (henceforth Levy) and Yu et al. US20210179145A1 (henceforth Yu).
Regarding claim 1,
Shen discloses:
A method performed by an apparatus of a vehicle, (See at least Fig. 2) the method comprising:
obtaining, via a camera of the vehicle, an image of an exterior view from the vehicle; (See at least Fig. 2, step 202, Para. 0032, “At step 202, system 100 receives a high resolution image and one or more pieces of data relating to the image (e.g., as illustrated in FIG. 4). In some embodiments, the high resolution image is a frame or image generated as the output of a camera.” The image of the exterior view from the vehicle is obtained.)
generating a cropped image of a distant region in the obtained image; performing first object recognition on the cropped image of the distant region by inputting the cropped image into a first object recognition network, wherein the cropped image has an original resolution of the obtained image; (See at least Fig. 4, step 206, Para. 0036, “At step 206, system 100 crops the priority FOV to generate a high resolution crop of the image (example shown in FIG. 4). As used herein, a “crop” is a predetermined segment or portion of the image…The high resolution crop preferably has the same resolution as the raw image”. A cropped image of a distant region (see Fig. 4, wherein the distant region comprises two cars ahead), wherein the cropped image has the same resolution of the obtained image. Further see Para. 0039, wherein the detector performs a first object recognition on the cropped image.)
performing second object recognition on a processed image associated with the obtained image, wherein the processed image has a down-sampled resolution of the obtained image; (See at least Para. 0037, “a low resolution version of the original image with a large, down sampled field of vision”, the image has a down-sampled resolution of the obtained image. The detector 212 performs a second objected recognition of the image.)
performing third object recognition by matching a result of the first object recognition with a result of the second object recognition; (See at least Fig. 5, and Para. 0038-0039, wherein the two images from the first and second object recognition via the detector 212 includes combining the outputs to remove duplicates. A result of the first object detection is matched with a result of the second object detection. Additionally, see Para. 0043, wherein the output from the high-resolution crop with the output of the low resolution image is aligned (i.e. matched).)
and controlling, based on a result of the third object recognition, an autonomous driving operation of the vehicle. (See at least Para. 0039, “The output may be usable by the system 100, or another system of one or more processors, to drive, and/or otherwise control operation of, an autonomous vehicle.” Additionally, see Para. 0059, wherein the output 516 is used in autonomous navigation, driving, and operation of the vehicle.)
Shen does not specifically state wherein an object in the cropped image is maintained to be equal to or larger than a minimum recognizable size in the first object recognition network. However, Levy teaches:
wherein an object in the cropped image is maintained to be equal to or larger than a minimum recognizable size in the first object recognition network. (See at least Fig. 1 and Para. 0022, “In some aspects, the object detector used in the second stage (henceforth referred to as the second object detector) may be different from the object detector used in the first stage (henceforth referred to as the first object detector). More specifically, the second object detector may be a faster detector that processes smaller images. For example, but not limited hereto, the input image for the second object detector may need to be 96×96 pixels in size (compared to 384×224 pixels of the first object detector). The object detection component may process input image 108 (e.g., crop, pad, resize, etc.,) to yield second-stage processed image 110, which has the required dimensions for the second object detector” and Para. 0039, “if the second input image already meets the dimensional requirements of the second object detector, second-stage input image 108 may be directly provided as an input of the second object detector”. The object in the cropped image is maintained to be equal or larger than a minimum recognizable size for the object recognition network.)
It would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to have modified Shen to incorporate the teachings of Levy to include the limitation as recited above since “while there are many deep-learning object detectors available, it is difficult to achieve fast and accurate detections on small objects in images. If an object is too small in an image, for example, the object and/or its features may not be properly identified” (Para. 0002, Levy). This would create a more robust system for an object in an image to be properly identified and would improve object detection systems. Additionally, a person having ordinary skill in the art would have a reasonable expectation of success in combining the teachings of Shen and Levy. The claimed invention is merely a combination of known elements and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art before the effective filing date of the claimed invention would have recognized that the results of the combination would have been predictable.
Shen does not specifically state wherein the controlling the autonomous driving operation of the vehicle comprises performing at least one of a minimum risk maneuver (MRM) operation to reduce a risk of collision or a biased driving operation maintaining a distance from an adjacent object.
However, Yu teaches:
wherein the controlling the autonomous driving operation of the vehicle comprises performing at least one of a minimum risk maneuver (MRM) operation to reduce a risk of collision or a biased driving operation maintaining a distance from an adjacent object. (See at least Para 0042, “a minimum risk maneuver (MRM) may be performed to protect the driver and the vehicle and minimize occurrence of a collision with a surrounding vehicle”. The autonomous vehicle is controlled to perform a minimum risk maneuver to reduce a risk of collision with a surrounding vehicle.)
It would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to have modified Shen to incorporate the teachings of Yu to include the limitation as recited above since “ it is generally preferable for the authority to operate the vehicle be switched to a driver rather than a system which operates autonomous driving. However, there may be situation when this switch is not possible, and, in such a case, a minimum risk maneuver (MRM) may be performed to protect the driver and the vehicle and minimize occurrence of a collision with a surrounding vehicle” (Para. 0042, Yu). Therefore, it would increase the safety of the driver to perform a MRM when a switch from autonomous to manual driving is not possible. Additionally, a person having ordinary skill in the art would have a reasonable expectation of success in combining the teachings of Shen and Yu. The claimed invention is merely a combination of known elements and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art before the effective filing date of the claimed invention would have recognized that the results of the combination would have been predictable.
Regarding claim 3,
Shen discloses:
wherein the performing of the second object recognition comprises inputting the processed image having the down-sampled resolution into a second object recognition network. (See at least Para. 0039, wherein the down-sampled image is input into a neural network for object detection. Additionally see Para. 0039, “The images (e.g., for the same frame) can be fed into the same detector, two parallel instances of the same detector, different detectors (e.g., one for the high-resolution crop, one for the low-resolution full image), or otherwise processed“, wherein a second object recognition network is used for inputting the down-sampled resolution image.)
Regarding claim 6,
Shen discloses:
wherein the generating of the cropped image comprises: determining a vanishing point in the obtained image; and determining the distant region by determining a region of interest that comprises the vanishing point.
(See at least Para. 0024, wherein a vanishing line (i.e. a line is a variety of points) is determined such that the region of interest comprises the vanishing point.)
Regarding claim 12,
Shen, Levy, and Yu discloses the same limitations as recited in claim 1 above, and is therefore rejected under the same rational.
Regarding claim 14,
Shen, Levy, and Yu discloses the same limitations as recited in claim 3 above, and is therefore rejected under the same rational.
Regarding claim 17,
Shen, Levy, and Yu discloses the same limitations as recited in claim 6 above, and is therefore rejected under the same rational.
Claims 4-5 and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Shen, Levy, and Yu further in view of GomezCaballero et al. US20190026918A1 (henceforth GomezCaballero).
Regarding claim 4,
Shen, Levy, and Yu discloses the limitations as recited in claims 1 and 2 above.
Shen does not specifically state wherein the performing of the first object recognition further comprises determining, based on information associated with the vehicle, whether recognition of a distant object is necessary.
However, GomezCaballero teaches:
wherein the performing of the first object recognition further comprises determining, based on information associated with the vehicle, whether recognition of a distant object is necessary. (See at least Para. 0053, wherein a weight of the priority for the far object recognition processing and the near object recognition is determined based on analyzing road features at the location of the vehicle (i.e. based on information associated with the vehicle). Additionally, see Para. 0056-0057, wherein the vehicle data is used to determine the weight of the priority for the far/near object recognition processing. Therefore, it is determined whether recognition of a distant object is necessary a (i.e. low far object recognition priority).)
It would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to have modified Shen to incorporate the teachings of GomezCaballero to include the limitation as recited above such that “non-recognition rates of objects in both the near and far regions can be reduced. As a result, traveling safety can be improved” (Para. 0012, GomezCaballero). This would create a more robust object detection system, by setting priorities with regards to far object recognition processing and near object recognition processing. Additionally, a person having ordinary skill in the art would have a reasonable expectation of success in combining the teachings of Shen and GomezCaballero. The claimed invention is merely a combination of known elements and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art before the effective filing date of the claimed invention would have recognized that the results of the combination would have been predictable.
Regarding claim 5,
Shen does not specifically state wherein the information associated with the vehicle comprises at least one of: location information, speed information, steering information, or heading indication information.
However, GomezCaballer teaches:
wherein the information associated with the vehicle comprises at least one of: location information, speed information, steering information, or heading indication information. (See at least Para. 0056-0057, wherein the vehicle data such as speed information is used to determine the weight of the priority for the far/near object recognition processing._
It would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to have modified Shen to incorporate the teachings of GomezCaballero to include the limitation as recited above such that “non-recognition rates of objects in both the near and far regions can be reduced. As a result, traveling safety can be improved” (Para. 0012, GomezCaballero). This would create a more robust object detection system, by setting priorities with regards to far object recognition processing and near object recognition processing. Additionally, a person having ordinary skill in the art would have a reasonable expectation of success in combining the teachings of Shen and GomezCaballero. The claimed invention is merely a combination of known elements and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art before the effective filing date of the claimed invention would have recognized that the results of the combination would have been predictable.
Regarding claim 15,
Shen, Levy, Yu and GomezCaballero discloses the same limitations as recited in claim 5 above, and is therefore rejected under the same rejection and obviousness rational.
Regarding claim 16,
Shen, Levy, Yu, and GomezCaballero discloses the same limitations as recited in claim 6 above, and is therefore rejected under the same rejection and obviousness rational.
Claims 7-8 and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Shen, Levy, and Yu further in view of Zhang et al. US20190082156A1 (henceforth Zhang).
Regarding claim 7,
Shen, Levy, and Yu discloses the limitations as recited in claims 1 and 6 above.
Shen further discloses:
setting the vanishing point as a reference point for the region of interest having the original resolution. (See at least Para. 0024, wherein the vanishing point is set for the region of interest having the original resolution (see at least Para. 0034).)
However, Shen does not specifically state setting, based on camera calibration information of the vehicle, the vanishing point.
However, Zhang teaches:
setting, based on camera calibration information of the vehicle, the vanishing point. (See at least Para. 0007, “calibrating intrinsic parameters of a set of cameras; extracting corner points associated with a pattern; and computing a vanishing point based on information on the extracted corner points.” The vanishing point is set based on the camera calibration information of the vehicle.)
It would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to have modified Shen to incorporate the teachings of Zhang to include the limitation as recited above such that the optical axes of a camera can be aligned (Para. 0007, Zhang). This would create a more robust system for setting up a camera on a vehicle. Additionally, a person having ordinary skill in the art would have a reasonable expectation of success in combining the teachings of Shen and Zhang. The claimed invention is merely a combination of known elements and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art before the effective filing date of the claimed invention would have recognized that the results of the combination would have been predictable.
Regarding claim 8,
Shen further discloses:
wherein the determining of the distant region further comprises storing scaling information of the region of interest with the original resolution.
(See at least Para. 0024, wherein the heuristics database stores a set of heuristics to identify the desired field of view, including a predetermined dimension (i.e. storing information).)
Regarding claim 18,
Shen and Zhang discloses the same limitations as recited in claim 7 above, and is therefore rejected under the same rejection and obviousness rational.
Regarding claim 19,
Shen and Zhang discloses the same limitations as recited in claim 8 above, and is therefore rejected under the same rejection and obviousness rational.
Claims 9-11 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Shen, Levy, and Yu further in view of Schulte et al. US20180300884A1 (henceforth Schulte)
Regarding claim 9,
Shen, Levy, and Yu discloses the limitations as recited in claim 1 above.
Shen further discloses:
wherein the performing of the first object recognition comprises receiving, based on a first object recognition network, a first object recognition map of the distant region. (See at least Para. 0018, “it may be appreciated that the percentage of the image cropped may be adjusted. For example, a central fourth of the image may be taken. As another example, a machine learning model may be used to identify a particular strip along a horizontal axis of the image which corresponds to a horizon or other vanishing line. In some embodiments, map data may be used.” Further see Para. 0033-0034.)
Shen does not specifically state a “a first object recognition heat map of the distant region”. However, Schulte teaches:
a first object recognition heat map of the distant region
(See at least Para. 0041, “FPA 104 of IR imaging module 102 may be configured to detect IR radiation from a scene 140 for a field of view (FOV) of FPA 104, and provide IR image data (e.g., via analog or digital signals) representing the IR radiation in response to detecting the IR radiation”. A heat map of a distant region is determined to identify objects in a scene.)
It would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to have modified Shen to incorporate the teachings of Schulte to include the limitation as recited above since “the average pixel intensities may advantageously be used to separate objects from each other. As can be observed in the two profile lines of horizontal profile 704 and vertical profile 706, objects may be separated from each other based on the local minimums” (Para. 0070, Schulte), which would create a more robust object recognition system for separating objects from each other. Additionally, a person having ordinary skill in the art would have a reasonable expectation of success in combining the teachings of Shen and Schulte. The claimed invention is merely a combination of known elements and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art before the effective filing date of the claimed invention would have recognized that the results of the combination would have been predictable.
Regarding claim 10,
Shen further discloses:
wherein the performing of the second object recognition comprises receiving a second object recognition map for an overall region of the obtained image. (See at least Para. 0037, “a low resolution version of the original image with a large, down sampled field of vision”, the image has a down-sampled resolution of the obtained image. The detector 212 performs a second objected recognition of the image.)
Shen does not specifically state a “second object recognition heat map for an overall region”. However, Schulte teaches:
second object recognition heat map for an overall region
(See at least Para. 0046, “FPA 104 may detect IR radiation received from scene 140 that only includes background 142 along optical path 150 for a FOV. In response, ROIC 114 may generate thermal image data (e.g., a thermal image) of background 142.” A second object recognition heat map is determined for an overall region.)
It would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to have modified Shen to incorporate the teachings of Schulte to include the limitation as recited above since “the average pixel intensities may advantageously be used to separate objects from each other. As can be observed in the two profile lines of horizontal profile 704 and vertical profile 706, objects may be separated from each other based on the local minimums” (Para. 0070, Schulte), which would create a more robust object recognition system for separating objects from each other. Additionally, a person having ordinary skill in the art would have a reasonable expectation of success in combining the teachings of Shen and Schulte. The claimed invention is merely a combination of known elements and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art before the effective filing date of the claimed invention would have recognized that the results of the combination would have been predictable.
Regarding claim 11,
Shen further discloses:
wherein the performing of the third object recognition comprises: generating an aligned map by: scaling the first object recognition map of the distant region according to scaling information of the distant region;
(See at least Para. 0042, “scaling the high-resolution crop's detected objects down (or the low-resolution image's detected objects up) based on the scaling factor between the high-resolution crop (priority FOV) and the full image”. A first object recognition map is scaled according to scaling information of the distant region.)
and matching the scaled first object recognition map with the second object recognition map for the overall region; and performing, based on the aligned map, the third object recognition.
(See at least Para. 0043, “ aligning the output from the high-resolution crop with the output of the low-resolution image during output combination. The outputs are preferably aligned based on the location of the high-resolution crop (priority FOV) relative to the full image, but can be otherwise aligned. The outputs are preferably aligned after scaling”. Further see Para. 0044, wherein duplicates are detected and removed based on the aligned map (i.e. a third object recognition).)
Shen does not specifically state generating an aligned heat map by matching the scaled first object recognition heat map with the second object recognition heat map for the overall region.
However, Schulte teaches:
generating an aligned heat map by matching the scaled first object recognition heat map with the second object recognition heat map for the overall region (See at least Para. 0037, 0041, and 0046-0047, wherein two heat maps (i.e. the scaled first object recognition heat map (Para. 0041) and the second object recognition heat map) are aligned by calibrating one heat map to the other.)
It would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to have modified Shen to incorporate the teachings of Schulte to include the limitation as recited above since “the average pixel intensities may advantageously be used to separate objects from each other. As can be observed in the two profile lines of horizontal profile 704 and vertical profile 706, objects may be separated from each other based on the local minimums” (Para. 0070, Schulte), which would create a more robust object recognition system for separating objects from each other, and would improve the third object recognition. Additionally, a person having ordinary skill in the art would have a reasonable expectation of success in combining the teachings of Shen and Schulte. The claimed invention is merely a combination of known elements and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art before the effective filing date of the claimed invention would have recognized that the results of the combination would have been predictable.
Regarding claim 20,
Shen and Schulte discloses the same limitations as recited in claim 9 as recited above, and is therefore rejected under the same rejection and obviousness rational.
Claim 21 is rejected under 35 U.S.C. 103 as being unpatentable over Shen, Levy, Yu and GomezCaballero further in view of Luders US20190176829A1.
Regarding claim 21,
Shen, Levy, Yu and GomezCaballero discloses the limitations as recited in claims 12 and 15 above. Shen does not specifically state wherein the at least one processor is configured to execute the computer-readable instructions to cause the vehicle to determine that recognition of a distant object is necessary in response to the vehicle being in a driving environment in which an average vehicle speed is higher than a threshold speed or in response to the vehicle making a turn at an intersection.
However, Luders teaches:
wherein the at least one processor is configured to execute the computer-readable instructions to cause the vehicle to determine that recognition of a distant object is necessary in response to the vehicle being in a driving environment in which an average vehicle speed is higher than a threshold speed or in response to the vehicle making a turn at an intersection
(See at least Fig. 8 and Para. 0055, “as the vehicle 100 makes a left turn through intersection 854 and into roadway 850, there is some risk that a vehicle traveling towards the intersection 854, such as the vehicle 800, will collide with the vehicle 100 if the vehicle 100 enters the intersection 854. Accordingly, the vehicle 100 detects whether any vehicles are approaching to avoid such a collision. To give the vehicle 100 as much notice as possible, the vehicle 100 detects whether any objects are within the first sensor range 315. Accordingly, the vehicle 100 may detect at least a portion of the vehicle 800. In response, the vehicle 100 may continue to wait at the stop sign 852 until the field of view is clear.” As shown in Fig. 8, the vehicle determines that recognition of a distant object is necessary (i.e. using distant sensor range 315) in response to the vehicle making a turn at an intersection.)
It would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to have modified Shen to incorporate the teachings of Luders to include the limitation as recited above since “there is some risk that a vehicle traveling towards the intersection 854, such as the vehicle 800, will collide with the vehicle 100 if the vehicle 100 enters the intersection 854” (Para. 0055, Luders) and “By observing and adhering to noisy signals at an outer bounds of a sensor range, the vehicle may take a precautionary action which results in safer operation of the vehicle. For example, as opposed to requiring an abrupt deceleration and stop when an object is detected at a closer range, the vehicle may prepare by ceasing acceleration. In addition to an improved riding experience for passengers of the vehicle, the precautionary actions of the vehicle increase the safety of everyone sharing the roadway.” (Para. 0058, Luders). This would create a more robust perception system in a vehicle, such that precautionary action can be taken by the vehicle without waiting for a more precise detection. Additionally, a person having ordinary skill in the art would have a reasonable expectation of success in combining the teachings of Shen and Luders. The claimed invention is merely a combination of known elements and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art before the effective filing date of the claimed invention would have recognized that the results of the combination would have been predictable.
Claim 22 is rejected under 35 U.S.C. 103 as being unpatentable over Shen, Levy, and Yu further in view of Kwon US20200184235A1 and Yohanandan et al. US20210150721A1 (henceforth Yohanandan).
Regarding claim 22,
Shen, Levy, and Yu discloses the limitations as recited in claim 12 above.
Shen does not specifically state wherein the first object recognition network is located in a server external to the vehicle and wherein the at least one processor is configured to execute the computer-readable instructions to cause the vehicle to perform the first object recognition by transmitting the image to the server.
However, Kwon teaches:
wherein the first object recognition network is located in a server external to the vehicle and wherein the at least one processor is configured to execute the computer-readable instructions to cause the vehicle to perform the first object recognition by transmitting the image to the server
(See at least Para. 0078 and 0084, wherein the object recognition network is located in a server external to the vehicle and the image is transmitted to the server to perform object recognition.)
It would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to have modified Shen to incorporate the teachings of Kwon to include the limitation as recited above in order to “provides an object recognition-based driving pattern managing server that recognizes an object based on big data and determines a driving pattern according to the type and attribute of the recognized object to diversify a vehicle control strategy” (Para. 0007, Kwon). This would create a more robust object recognition system and “for driving safety in the autonomous driving step of a vehicle” (Para. 0135, Kwon). Additionally, a person having ordinary skill in the art would have a reasonable expectation of success in combining the teachings of Shen and Kwon. The claimed invention is merely a combination of known elements and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art before the effective filing date of the claimed invention would have recognized that the results of the combination would have been predictable.
Shen and Kwon do not specifically state wherein the image that is transmitted is a cropped image having the original resolution.
However, Yohanandan teaches:
wherein the image that is transmitted is a cropped image having the original resolution. (See at least Fig. 4 and Para. 0040 “the image file may include full-resolution images, scaled images, or a combination of both” and Para. 0041,“method 400 transmits zones of interest at full-resolution, while the rest of the combined output image is down sampled.” Since the original image that is received (i.e. image 402) is at “full-resolution”, then the cropped image that is transmitted has the original resolution of the image.)
It would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to have modified Shen and Kwon to incorporate the teachings of Yohanandan to include the limitation as recited above in order to avoid false-positives and false-negatives (Para. 0003, Yohanandan) when recognizing an object. This would create a more robust object recognition system. Additionally, a person having ordinary skill in the art would have a reasonable expectation of success in combining the teachings of Shen, Kwon and Yohanandan. The claimed invention is merely a combination of known elements and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art before the effective filing date of the claimed invention would have recognized that the results of the combination would have been predictable.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kim et al US20210309217A1 discloses a processor to determine a travelling situation and a lane position, and determine an autonomous driving control maneuver of a vehicle depending on the determination result, and a non-transitory storage medium to store a result calculated by the processor and a set of instructions executed by the processor. The processor determines a safety of each lane of a road on which the vehicle is travelling to control the vehicle to stop on a lane representing a highest safety, after starting a minimum risk maneuver of the autonomous driving control maneuver. (See abstract).
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 GABRIEL J LAMBERT whose telephone number is (571)272-4334. The examiner can normally be reached M-F 10:00 am- 6:00 pm MDT.
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/Erin M Piateski/Supervisory Patent Examiner, Art Unit 3669
/G.J.L./
Examiner
Art Unit 3669
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