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 § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1 and 3-13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hofman (12,633,155) in view of Huang et al. (CN1312521A).
Regarding claim 1, Hofman discloses a device for monitoring a portion of road, comprising a single secure housing (col. 4, lines 26-29 and 53-55; col. 5, lines 49-54) containing at least:
a set of imaging apparatuses (110a, 110b, 110c) comprising a first camera configured according to a first orientation for obtaining at least one front image, a second camera configured according to a second orientation for obtaining a series of side images and a third camera configured according to a third orientation for obtaining at least one rear image of a vehicle present on said portion (col. 4, lines 43-51; col. 5, lines 62-67, col. 6, lines 1-2);
a processing platform (col. 4, lines 19-42) configured to detect a presence of said vehicle in said at least one image (col. 10, lines 5-10) and, in response to detecting the presence of said vehicle in the image, trigger said set of imaging apparatuses to obtain said series of side images (col. 10, lines 11-14), wherein no side images are taken in the absence of such detection,
associate each of said images with a time stamp (col. 9, lines 40-42),
determine an identifier for said vehicle, said identifier comprising, when a license plate number has been determined (col. 5, lines 11-15), said license plate number, and otherwise a detection index, said detection index being made up of a date and time resulting from said time stamps, and a number associated with a passage of said vehicle (according to col. 9, lines 40-42, the location can be represent by a number and the cropped license plate image can be either readable or not readable; when it is unreadable, this clause meets the claimed limitation),
match said images for said vehicle (col. 2, lines 23-47),
determine a number of passengers associated with said vehicle at least based on said series of side images, construct a file for said vehicle comprising said identifier, said images and said number of passengers, and transmit said file to a remote server (col. 2, lines 23-47; col.1, lines 19-23).
Hofman does not disclose that the operation of detecting the presence or absence of a vehicle is based on the front image as claimed. Instead, Hofman describes that the presence of the vehicle is determined based on the first image without specifying which camera generates the first image (col. 10, lines 5-10).
Huang, from the similar field of endeavor, teaches the use of a front camera (a warning camera) to trigger an identification camera when the presence of a vehicle is detected. By using the front camera, the captured image can preemptively warn the identification camera ahead of time so that the high resolution images can be captured on time.
Therefore, knowing the first image in Hofman is equivalent to the image generated by the warning camera in Huang, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to utilize the front camera, such as camera 110B, as the first image camera so that the camera 110A could capture the vehicle image precisely.
Regarding claim 3, Hofman discloses the processing platform is configured to detect the presence of a vehicle in said rear image (col. 5, lines 11-15) and then finalize said file for said transmission (note col. 9, lines 40-44).
Regarding claim 4, Hofman does not disclose that the processing platform is arranged to determine said number of passengers by subjecting at least one side image to a Yolo type convolution neural network. Instead, Hofman teaches that in certain implementations, the described technologies can be configured to identify occupants within a vehicle via various machine learning techniques such as convolutional neural networks (CNN) and/or other machine learning/deep learning techniques (col. 8, lines 30-34). The examiner takes Official Notice that Yolo type convolutional neural network is one type of well known convolutional neural networks. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to employ the well known Yolo type convolutional neural network as the convolutional neural network in Hofman to perform the well known functions as claimed.
Regarding claim 5, Hofman discloses the processing platform is furthermore configured to read the license plates present in said front and rear images in order to determine license plate numbers (note col. 5, lines 11-15).
Regarding claim 6, Hofman inherently discloses that each of said images is associated with a time stamp, said time stamp conforming to a synchronization provided by a synchronization server via an NTP protocol. That is, the images captured by the cameras are highly synchronized and time stamped (note network in Fig. 3).
Regarding claim 7, Hofman discloses said series of side images is taken in the near-infrared (note col. 4, lines 63-64).
Regarding claim 8, Hofman inherently discloses at least said series of side images is performed in collaboration with an illuminator adapted to trigger short-duration illumination in the imaging direction and at a frequency substantially equal to that of taking images (note col., 4, lines 52-62; 312 in Fig. 3).
Regarding claim 9, Hofman inherently discloses that the processing platform is configured to detect congestion on said road portion and, in this case, interrupt the obtaining of said series of side images. That is, the image capturing function in Hofman stops when there is no moving vehicle detected.
Regarding claim 10, Hofman discloses that the processing platform comprises at least one microprocessor and at least one memory containing computer code configured to operate said processing platform in collaboration with said at least one microprocessor (note Fig. 11).
Regarding claim 11, Hofman discloses a display apparatus for the vehicle, wherein the information displayed on said apparatus is determined from said file (note col. 14, lines 13-19).
Regarding claims 12 and 13, see similar rejections as set forth above.
Response to Arguments
Applicant's arguments filed 9/25/26 have been fully considered but they are not persuasive.
With respect to applicant’s argument that Hofman does not disclose the claimed single secure housing, the examiner disagrees. As set forth in the rejection above, the cameras, the light sources, and the executing devices can be integrated together in the camera housing and the cameras together can be placed on a single pole (col. 4, lines 26-29 and 53-55; col. 5, lines 49-54). Therefore, when interpreted broadly, Hofman meets the single secure housing as claimed.
As to applicant’s argument that Hofman fails to disclose configuring the processing platform to detect the presence of a vehicle in the claimed front image and, in response to that image-based detection, trigger acquisition of the series of side images, while taking no side images in the absence of such detection as claimed, the examiner disagrees. As set forth in the rejections above, Hofman teaches the use of image to detect the presence of a vehicle but does not specify which camera is being used. Col. 10, lines 5-10. Huang, a teaching reference originated from the similar field of endeavor, supports the use of a front warning camera to trigger a main identification camera to capture the high resolution images of the incoming vehicle. By using the warning camera, the identification camera is preemptively triggered to captured the incoming vehicle precisely. Since the selection of the front camera as the first image camera in Hofman would have been obvious in view Huang, the combination of Hofman and Huang clearly meets the claimed limitations.
Concerning applicant’s argument that Hofman does not disclose the claimed conditional vehicle-identifier logic and that amended claim 1 requires a specific alternative identifier scheme in which the license plate number is used when a license plate number has been determined, but, when it has not, the system instead generates a detection index comprising a date and time resulting from the image time stamps together with a number associated with the passage of the vehicle as claimed, the examiner disagrees. As set forth in the rejection above, the limitation is being rejected as follows:
determine an identifier for said vehicle, said identifier comprising, when a license plate number has been determined (col. 5, lines 11-15), said license plate number, and otherwise a detection index, said detection index being made up of a date and time resulting from said time stamps, and a number associated with a passage of said vehicle (according to col. 9, lines 40-42, the location can be represent by a number and the cropped license plate image can be either readable or not readable; when it is unreadable, this clause meets the claimed limitation).
Basically, the resulting image in Hofman always includes the count of occupants, the license plate cropped image, and date/time of the event. When the license plate is recognizable, the resulting image would include the counts of occupants, the license plate cropped image, and date/time of the event. When the license plate is unrecognizable, the resulting image would also include the counts of occupants, the license plate cropped image with unrecognizable characters, and the date/time of the event. Thus, when interpreted broadly, Hofman still meets the claimed invention.
In view of forgoing arguments, it is clear that applicant fails to overcome Hofman and Huang. As a result, the prior art rejection is maintained.
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 MICHAEL LEE whose telephone number 571-272-7349. The examiner can normally be reached on Monday through Thursday from 9:00 am to 6:00 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, John Miller, can be reached on 571-272-7353. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL LEE/ Primary Examiner,
Art Unit 2422
