# US 12,008,414 B2 · Information processing apparatus, information processing method, and information processing program > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,008,414 B2 - Document ID: US12008414B2 - Status: Granted - Kind: B2 - Application number: 17/439,743 - Filed: 2020-03-05 - Published: 2022-06-09 - Granted: 2024-06-11 - Earliest claimed: 2019-03-22 - Assignees: Sony Semiconductor Solutions Corporation - Applicants: Sony Semiconductor Solutions Corporation - Inventors: Yuji Handa - Web page: https://patentgrep.com/patent/US12008414B2 ## CPC - G06F 9/5066: {Algorithms for mapping a plurality of inter-dependent sub-tasks onto a plurality of physical CPUs (mappping at compile time, see G06F8/451)} - B60W 60/001: {Planning or execution of driving tasks} - G01S 13/867: {Combination of radar systems with cameras} - G01S 13/931: of land vehicles - G06F 9/4806: {Task transfer initiation or dispatching} - G06F 9/4881: {Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues} - G06F 18/253: {of extracted features} - G06V 10/764: using classification, e.g. of video objects - G06V 10/80: Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level (multimodal speaker identification or verification G10L17/10) - G06V 10/806: {of extracted features} - G06V 10/82: using neural networks - G06V 10/87: {using selection of the recognition techniques, e.g. of a classifier in a multiple classifier system} - G06V 10/94: Hardware or software architectures specially adapted for image or video understanding - G06V 10/955: {using specific electronic processors} - G06V 10/96: Management of image or video recognition tasks - G06V 20/58: Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads - G06V 20/584: {of vehicle lights or traffic lights} - B60W 2420/40: Photo, light or radio wave sensitive means, e.g. infrared sensors - B60W 2420/403: Image sensing, e.g. optical camera - B60W 2420/408: Radar; Laser, e.g. lidar - B60W 2420/54: Audio sensitive means, e.g. ultrasound - G06V 2201/08: Detecting or categorising vehicles - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - B60W: CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT - G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING ## Abstract An information processing apparatus comprising, at least one first processor configured to carry out a first process on data input from at least one sensor to produce first processed data, a selector configured to select, according to a first predetermined condition, at least one of a plurality of second processes, and at least one second processor configured to receive the first processed data from the at least one first processor and to carry out the selected at least one of the plurality of second processes on the first processed data to produce second processed data, each of the plurality of second processes having a lower processing load than the first process. ## Claims ### Claim 1 An information processing apparatus comprising: at least one first processor configured to carry out a first process on data input from at least one sensor to produce first processed data; a selector configured to select, according to a first predetermined condition, at least one of a plurality of second processes; and at least one second processor configured to receive the first processed data from the at least one first processor and to carry out the selected at least one of the plurality of second processes on the first processed data to produce second processed data, each process of the plurality of second processes having a lower processing load than the first process. ### Claim 2 (depends on 1) The information processing apparatus according to claim 1, wherein the selector is configured to select at least one of the plurality of second processes according to a peripheral environmental condition as the first predetermined condition. ### Claim 3 (depends on 1) The information processing apparatus according to claim 1, wherein the at least one first processor is further configured to extract one or more features of the data input from the at least one sensor based, at least in part, on a feature extraction parameter that has been learned by a machine learning process. ### Claim 4 (depends on 3) The information processing apparatus according to claim 3, further comprising: at least one storage unit configured to store a plurality of feature extraction parameters different from each other, wherein the at least one first processor is further configured to select, according to a second predetermined condition, the feature extraction parameter from the plurality of feature extraction parameters stored in the at least one storage unit. ### Claim 5 (depends on 4) The information processing apparatus according to claim 4, wherein the feature extraction parameter is selected from the plurality of feature extraction parameters stored in the at least one storage unit according to a peripheral environmental condition as the second predetermined condition. ### Claim 6 (depends on 5) The information processing apparatus according to claim 5, wherein the feature extraction parameter is selected from the plurality of feature extraction parameters stored in the at least one storage unit according to weather information. ### Claim 7 (depends on 1) The information processing apparatus according to claim 1, wherein the at least one second processor is further configured to determine an object detected by the at least one sensor based, at least in part, on a determination parameter that has been learned by a machine learning process. ### Claim 8 (depends on 7) The information processing apparatus according to claim 7, further comprising: at least one storage unit configured to store a plurality of determination parameters different from each other, wherein the at least one second processor is further configured to select, according to the first predetermined condition, the determination parameter from the plurality of determination parameters stored in the at least one storage unit. ### Claim 9 (depends on 7) The information processing apparatus according to claim 7, wherein the at least one sensor includes a first sensor and a second sensor, and the at least one first processor is further configured to: receive first data from the first sensor; and receive second data from the second sensor; carry out the first process on the first data and the second data to produce the first processed data; and provide the first processed data to the at least one second processor. ### Claim 10 (depends on 9) The information processing apparatus according to claim 9, wherein the first sensor is an image sensor, and the second sensor is at least one of a millimeter-wave radar, a light detection and ranging sensor, or an ultrasonic sensor. ### Claim 11 (depends on 7) The information processing apparatus according to claim 7, wherein the at least one second processor is configured to determine an object detected by the at least one sensor based, at least in part, on a determination model that has been trained by a machine learning process. ### Claim 12 (depends on 1) The information processing apparatus according to claim 1, wherein the selector is configured to select at least one of the plurality of second processes according to a time of day as the first predetermined condition. ### Claim 13 (depends on 1) The information processing apparatus according to claim 1, wherein the information processing apparatus is mounted on a vehicle. ### Claim 14 (depends on 13) The information processing apparatus according to claim 13, wherein the at least one second processor is further configured to determine an object detected by the at least one sensor based, at least in part, on a determination parameter that has been learned by a machine learning process, and output a signal based, at least in part, on the determined object to at least one of an Advanced Driver Assistance System or an automatic drive system of the vehicle. ### Claim 15 (depends on 1) The information processing apparatus according to claim 1, wherein the at least one first processor comprises an FPGA, and the at least one second processor comprises at least one of an FPGA, a CPU, a DSP, or a GPU. ### Claim 16 (depends on 1) The information processing apparatus according to claim 1, wherein the first process comprises a multi-dimensional product-sum operation, and the second process comprises a classification of an object or recurrence. ### Claim 17 (depends on 1) The information processing apparatus according to claim 1, wherein the plurality of second processes are different from each other. ### Claim 18 An information processing method that is carried out by a computer, the method comprising: performing a first process on data input from at least one sensor to produce first processed data; selecting, according to a predetermined condition, at least one of a plurality of second processes, wherein the plurality of second processes are different from each other and each process of the plurality of second processes has a lower processing load than the first process; and performing the selected at least one of the plurality of second processes on the first processed data to produce second processed data. ### Claim 19 At least one non-transitory computer-readable storage medium storing processor executable instructions that, when executed by at least one computer hardware processor, cause the at least on computer hardware processor to preform: a first processing sequence that performs a first process on data input from at least one sensor to produce first processed data; a selecting sequence that selects, according to a predetermined condition, at least one of a plurality of second processes, wherein the plurality of second processes are different from each other and each process of the plurality of second processes has a lower processing load than the first process; and a second processing sequence that performs the selected at least one of the plurality of second processes on the first processed data to produce second processed data.