DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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 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.
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 of this title, 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, 6-7 and 9-11 are rejected under 35 U.S.C. 103 as being unpatentable over Pollach et al. US2018/0068206 in view of Pollach in view of Golov US2020/0156651.
As per Claim 1, Pollach teaches a device for improving object recognition performance of an autonomous driving controller,
the device comprising an object recognition module unit (100) configured to: receive raw data from multiple sensors to recognize an object; infer information and/or classify an object. Data from or associated with sensor modalities (e.g., multi-level and multi-sensor data) may include, for example, raw sensor data 610, fused data 620, low level image features 630, high level data 640, data from external sources 650, and/or other relevant data. The raw sensor data 610 may include, for example, raw image data (e.g., pixels) from an image capture device, raw Radar reflection data, raw Lidar reflectivity data, raw ultrasonic data, high frequency analog data, and/or other raw data collected by a sensor on a vehicle. As described in detail herein, fused sensor data and/or events 620 may include a combination of data, such as raw sensor data, object-level data, and/or other data, from multiple sensors. The fused sensor data and/or events 620 may relate to, for example, a detection event and/or a region of interest”)
mark a raw data area, in which the object is present, (Pollach, Paragraph [0042]) as an intensive processing area and control the intensive processing area to be reflected in the raw data received from the multiple sensors. (Pollach, Paragraph [0015], “The object recognition and classification techniques disclosed herein can employ machine learning approaches. Many typical object classification approaches evaluate data from one sensor. Other typical approaches use one type of sensor data (e.g., Radar data) as a hint to assist classification on data from another sensor (e.g., raw image data). In contrast to these existing approaches, the object recognition and classification techniques disclosed herein classify objects based on data from multiple modalities, such as multiple sensors, multiple levels of sensor data, higher level data, tracked objects, objects from smart sensors, pre-processed data, and/or external data sources”)
Pollach does not explicitly teach information about a position and a type of the object
Golov teaches information about a position and a type of the object (Golov, Paragraph [0036], “In one embodiment, the autonomous vehicle includes sensors that collect sensor data. A non-volatile memory device of the vehicle is used to receive various data to be stored (e.g., raw sensor data and/or results from processing of raw sensor data, such as data regarding a type or position of a detected object). One or more computing devices can control the operation of the vehicle. At least one of these computing devices is used to control collection, by the non-volatile memory device, of data generated by the vehicle during operation”)
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Golov into Pollach because by utilizing the position and type of the object will assist Pollach in object classification and tracking.
Therefore it would have been obvious to one of ordinary skill to combine the two references to obtain the invention in Claim 1.
As per Claim 2, Pollach in view of Golov teaches the device of claim 1, wherein the object recognition module unit (100) is configured to output a preconfigured vehicle control signal to a vehicle in response to the recognized object information. (Pollach, Paragraph [0030]-[0031], “The autonomous driving system 100 can include a vehicle control system 130 to receive the control signals 131 from the driving functionality system 120. The vehicle control system 130 can include mechanisms to control operation of the vehicle, for example by controlling different functions of the vehicle, such as braking, acceleration, steering, parking brake, transmission, user interfaces, warning systems, or the like, in response to the control signals.“)
The rationale applied to the rejection of claim 1 has been incorporated herein.
As per Claim 3, Pollach in view of Golov teaches the device of claim 2, wherein the object recognition module unit (100) comprises: a recognition control unit (110) configured to receive raw data from multiple sensors, infer information about a position and a type of an object from raw data from each sensor by using a predetermined inference program, merge the inferred object recognition information for each sensor to recognize the object, mark a raw data area, in which the object is present, as an intensive processing area, and control the intensive processing area to be reflected in the raw data received from the multiple sensors; and a determination control unit (120) configured to output a preconfigured vehicle control signal to a vehicle in response to the recognized object information. (Pollach, Paragraph [0030]-[0031], [0042], [0063])
The rationale applied to the rejection of claim 2 has been incorporated herein.
As per Claim 6, Claim 6 claims an a method for utilizing the device as claimed in Claim 1. Therefore the rejection and rationale are analogous to that made in Claim 1.
As per Claim 7, Claim 7 claims the same limitation as Claim 2 and is dependent on a similarly rejected independent claim. Therefore the rejection and rationale are analogous to that made in Claim 2.
As per Claim 9, Pollach in view of Golov teaches the method of claim 7, wherein step b) comprises: step b-1) in which in case that the inferred object recognition information for each sensor is received, the recognition control unit (110) determines whether the object recognition information comprises information about an object type; and step b-2) in which in case that, as a result of the determination, the object recognition information comprises the information about the object type, the recognition control unit (110) updates object information recognized by merging the inferred object recognition information for each sensor, and controls a preconfigured vehicle control signal to be output in response to the recognized object information. (Pollach, Paragraph [0030]-[0031], [0042], [0063])
The rationale applied to the rejection of claim 7 has been incorporated herein.
As per Claim 10, Pollach in view of Golov teaches the method of claim 9, further comprising step b-3) in which in case that, as a result of the determination in step b-1), the object recognition information does not comprise the information about the object type, the recognition control unit (110) controls position information of the object to be reflected in an intensive processing area of raw data received from the sensor. (Golov, Paragraph [0036] and Pollach, Paragraph [0030]-[0031], [0042], [0063])
The rationale applied to the rejection of claim 9 has been incorporated herein.
As per Claim 11, Pollach in view of Golov teaches the method of claim 10, wherein step b-3) further comprises step in which the recognition control unit (110) analyzes the position information of the object to determine whether the position information is identical to a previously configured intensive processing area, and, in case that the position information of the object is determined to be different from the previously configured intensive processing area, updates the intensive processing area of the raw data and configures the updated intensive processing area to be reflected in preprocessing. (Golov, Paragraph [0036] and Pollach, Paragraph [0030]-[0031], [0042], [0063])
The rationale applied to the rejection of claim 10 has been incorporated herein.
Claims 4-5 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Pollach et al. US2018/0068206 in view of Pollach in view of Golov US2020/0156651 as applied to Claims 3 and 7 and further in view of Chiu US2008/0018753.
As per Claim 4, Pollach in view of Golov teaches the device of claim 3,
Pollach in view of Golov does not explicitly teach wherein the recognition control unit (110) comprises: a sensor processing unit (111) configured to preprocess raw data received from each sensor according to a preconfigured data size and format;
Chiu teaches wherein the recognition control unit (110) comprises: a sensor processing unit (111) configured to preprocess raw data received from each sensor according to a preconfigured data size and format; (Chiu, Abstract, “A method for modifying images by a way of capturing raw image data, includes: capturing raw image data; storing the raw image data in a storage unit; reading the raw image from the storage unit; modifying the image's size and parameters for the raw image data via an image processing unit; and transforming the modified raw image data into an image file with a predetermined format”)
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Chiu into Pollach in view of Golov because by standardizing the raw data to a standard size and format will ease the future processing of the data in Pollach.
Therefore it would have been obvious to one of ordinary skill to combine the three references to obtain the invention in Claim 3.
As per Claim 5, Pollach in view of Golov and Chiu teaches the device of claim 4, wherein the sensor comprises one among a radar, a LIDAR, a camera, a 3D shape recognition sensor, a laser sensor, and a multi-axis motion sensor. (Pollach, Paragraph [0047])
The rationale applied to the rejection of claim 4 has been incorporated herein.
As per Claim 8, Pollach in view of Golov teaches the method of claim 7,
wherein step a) comprises: step a-1) in which in case that raw data is received from each sensor, the recognition control unit (110) determines whether an intensive processing area of the raw data has been configured; step a-2) in which based on the determination result, the recognition control unit (110)
Pollach in view of Golov does not explicitly teach preprocesses the intensive processing area of the raw data according to a preconfigured data size and format
Chiu teaches preprocesses the intensive processing area of the raw data according to a preconfigured data size and format(Chiu, Abstract, “A method for modifying images by a way of capturing raw image data, includes: capturing raw image data; storing the raw image data in a storage unit; reading the raw image from the storage unit; modifying the image's size and parameters for the raw image data via an image processing unit; and transforming the modified raw image data into an image file with a predetermined format”)
Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the teachings of Chiu into Pollach in view of Golov because by standardizing the raw data to a standard size and format will ease the future processing of the data in Pollach.
Therefore it would have been obvious to one of ordinary skill to combine the three references to obtain the invention in Claim 8.
Conclusion
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/MING Y HON/Primary Examiner, Art Unit 2666
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