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 .
Response to Amendment
The Amendment filed 10/15/2025 has been entered. No claims have been added. Claim 8 has been cancelled. Claim 1 has been amended. Claims 1-7 and 9-15 remain pending in the application.
Response to Arguments
Applicant’s arguments, see pages 5-8, filed 10/15/2025, with respect to the 103 rejections of previously dependent claim 8 now amended into independent claim 1 have been fully considered but are not persuasive.
Examiner cannot concur the combination of Hu and Costin fail to disclose or suggest the amended claim language. FIG. 2 of Costin illustrates in internal components of sensor data distributors which include deserializers. It is well known in the art and to person of ordinary skill in the art that a deserializer reverses the operation of a serializer. The combination of Hu and Costin, through use of serializers and deserializers, discloses the concept of separating combined sensor data of a plurality of image sensors (by a serializer) to separate the combined image sensor data into respective image sensor data (by a deseralizer). The previous 103 rejection of dependent claim 8 also acknowledged Hu discloses a deserializer, see 801 of FIG. 9. Therefore, the rejection of now independent claim 1 over the combination of Hu and Costin.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/04/2025 and 11/18/2025 were considered by the examiner.
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.
Claims 1-3, 5-7, and 10-12 are rejected under 35 U.S.C. 103 as being unpatentable over Hu et al. US 2021/0056306 A1, hereafter Hu in view of Costin et al. US 2019/0250611 A1, hereafter Costin.
Regarding claim 1, Hu discloses a vehicle cabin sensing system (systems…sensors used to detect those occupants) [abstract] comprising:
an electronic control unit (AI supercomputer; advanced SoC 902) [0090; FIG. 9];
a camera system (autonomous vehicle) [0089] comprising:
multiple image sensors (one or more cameras (72, 73, 74, 75) deployed around the vehicle) [0082], wherein each image sensor provides respective sensor data (provide coverage of the driver and other occupants) [0082];
a combination circuit (serializer (906)) [0091; FIG. 9] configured to combine the sensor data provided by the image sensors into combined sensor data (see video data and fsync lines into serializer 906 from 912 and 943) [FIG. 9]; and
an interface (serializer (906)) [0091; FIG. 9] configured to transmit the combined sensor data to the electronic control unit (see transmission GMSL link from 906 to 901) [FIG. 9];
wherein the electronic control unit is configured to receive the combined sensor data and to perform vehicle cabin sensing using the combined sensor data (the neural networks preferably are trained to detect a number of different features and events, including: the presence of a face (5001)) [0083].
However, while Hu discloses a serializer and deserializer for the sensor data [801 and 906 of FIG. 9], Hu fails to explicitly disclose a processor configured to separate the combined sensor data into the respective sensor data provided by the respective image sensors and to perform the vehicle cabin sensing using the sensor data provided by the image sensors.
Costin, in an analogous environment, discloses a processor configured to separate the combined sensor data into the respective sensor data provided by the respective image sensors and to perform the vehicle cabin sensing using the sensor data provided by the image sensors (a sensor data distributor in each controller can aggregate input data to the sensor data distributor of the other controller under the same, pre-converted data interface…convert the aggregated input data to different output data interface to is used by the SoCs for processing…implemented as a SerDes; deserializer 226, deserializer 256) [0040; FIG. 2].
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use separation of sensor data, as disclosed by Costin, with the invention disclosed by Hu, the motivation being lower costs [0004].
Regarding claim 2, Hu and Costin address all of the features with respect to claim 1 as outlined above.
Hu further discloses the image sensors are operable to capture image data in different electromagnetic spectra (IR Image Sensor (912), RGB Image Sensor (918)) [0091].
Regarding claim 3, Hu and Costin address all of the features with respect to claim 1 as outlined above.
Hu further discloses the image sensors include at least two of a near-infrared image sensor, a longwave infrared or thermal image sensor, a depth image sensor and a colour image sensor (IR Image Sensor (912), RGB Image Sensor (918)) [0091].
Regarding claim 5, Hu and Costin address all of the features with respect to claim 1 as outlined above.
Hu further discloses the interface is configured to transmit the combined sensor data stream to the electronic control unit via serial data communication (serializer; see GMSL link and GSML deserializer) [0094].
Regarding claim 6, Hu and Costin address all of the features with respect to claim 1 as outlined above.
Hu further disclose the interface comprises a Serializer/Deserializer and is configured to transmit the combined sensor data stream to the electronic control unit using the Serializer/Deserializer (serializer; see GMSL link and GSML deserializer) [0094].
Regarding claim 7, Hu and Costin address all of the features with respect to claim 1 as outlined above.
Hu further discloses performing vehicle cabin sensing comprises performing detection of at least one of the detection of the presence of persons or objects or both in the vehicle cabin, and the detection of activities in the vehicle cabin (the neural networks preferably are trained to detect a number of different features and events, including: the presence of a face (5001)) [0083].
Regarding claim 10, Hu and Costin address all of the features with respect to claim 1 as outlined above.
Hu further discloses a housing in which the multiple image sensors are arranged (single housing) [0089].
Regarding claim 11, Hu and Costin address all of the features with respect to claim 1 as outlined above.
Hu further discloses the camera system comprises one or more optical systems for the image sensors, wherein the one or more optical systems are arranged in the housing (multiple sensors in a single housing…IR+RGB) [0089].
Regarding claim 12, Hu and Costin address all of the features with respect to claim 1 as outlined above.
Hu further discloses a respective system for each image sensor, wherein, for each image sensor the respective optical system is arranged in the housing (multiple sensors in a single housing…IR+RGB) [0089].
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Hu in view of Kim KR 10-2020-0069585 (machine translation provided by Espace.net), hereafter Kim.
Regarding claim 4, Hu addresses all of the features with respect to claim 1 as outlined above.
However, Hu fails to explicitly disclose the image sensors include all of a near-infrared image sensor, a longwave infrared or thermal image sensor, a depth image sensor and a colour image sensor.
Kim, in an analogous environment, discloses the image sensors include all of a near-infrared image sensor, a longwave infrared or thermal image sensor, a depth image sensor and a colour image sensor (the image acquisition 110 may acquire one or more image information in a vehicle. At this time, the image information acquisition 110 may include an RGB camera, a Depth sensor and a ThermalIR sensor. However, various other types of camera, for example,…an infrared camera) [0025].
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to replace the multiple image sensors of Hu with the sensors of Kim, obtaining the predictable results more/different image sensor type combos.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Hu in view of Golston et al. US 20180251122 A1, hereafter Golston.
Regarding claim 9, Hu addresses all of the features with respect to claim 8 as outlined above.
However, while Hu discloses a serializer to combine data, Hu fails to explicitly disclose the processor is configured to perform the vehicle cabin sensing using data fusion of the sensor data.
Golston, in an analogous environment, discloses the processor is configured to perform the vehicle cabin sensing using data fusion of the sensor data (sensor fuser 142 may fuse multiple data types) [0067].
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to fuse the sensor data, as disclosed by Golston, with the invention disclosed by Hu, the motivation being using multiple sensors to determine occupant status [0067].
Claims 13-15 are rejected under 35 U.S.C. 103 as being unpatentable over Hu in view of Kang et al. US 2022/0114754 A1, hereafter Kang
Regarding claim 13, Hu addresses all of the features with respect to claim 1 as outlined above.
However, Hu fails to explicitly disclose the image sensors have different resolutions.
Kang, in an analogous environment, discloses the image sensors have different resolutions (a resolution of the color image 510 may be higher than a resolution of the IR image 515) [0100].
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the use the different resolutions, as disclosed by Kang, with the invention disclosed by Hu, yielding predictable results of sensors with different capture capability.
Regarding claim 14, Hu addresses all of the features with respect to claim 1 as outlined above.
However, Hu fails to explicitly disclose the multiple image sensors comprise a thermal image sensor and a colour image sensor, wherein the resolution of the colour image sensor is higher than the resolution of the thermal image sensor.
Kang, in an analogous environment, discloses the multiple image sensors comprise a thermal image sensor and a colour image sensor, wherein the resolution of the colour image sensor is higher than the resolution of the thermal image sensor (a resolution of the color image 510 may be higher than a resolution of the IR image 515) [0100].
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the use the different resolutions, as disclosed by Kang, with the invention disclosed by Hu, yielding predictable results of sensors with different capture capability.
Regarding claim 15, Hu addresses all of the features with respect to claim 1 as outlined above.
However, Hu fails to explicitly disclose the resolution of the colour image sensor is at least double or at least four times higher than the resolution of the thermal image sensor.
Kang, in an analogous environment, discloses the resolution of the colour image sensor is at least double or at least four times higher than the resolution of the thermal image sensor (a resolution of the color image 510 may be higher than a resolution of the IR image 515) [0100].
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the use the different resolutions, as disclosed by Kang, with the invention disclosed by Hu, yielding predictable results of sensors with different capture capability.
Citation of Pertinent Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Weyers et al. US 2021/0081689 A1 discloses determining an activity of an occupant of a vehicle
Conclusion
THIS ACTION IS MADE FINAL. 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 STEFAN GADOMSKI whose telephone number is (571)270-5701. The examiner can normally be reached Monday - Friday, 12-8PM EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jay Patel can be reached at 571-272-2988. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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STEFAN GADOMSKI
Primary Examiner
Art Unit 2485
/STEFAN GADOMSKI/Primary Examiner, Art Unit 2485