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公开(公告)号:US20240265804A1
公开(公告)日:2024-08-08
申请号:US18633672
申请日:2024-04-12
Applicant: ACUSENSUS IP PTY LTD
Inventor: Alexander Jannink
CPC classification number: G08G1/0175 , G06V10/60 , G06V20/54 , G08G1/054 , H04N5/33 , G06V20/625 , G06V2201/08
Abstract: A method for detecting an infringement by vehicle operator is described. The method comprises detecting a vehicle; receiving one or more image of at least a part of the vehicle operator; automatically analysing with a neural network the one or more captured received image to detect an infringing act; and providing the one or more captured received images comprising the detected infringing act to thereby detect the infringement. Also described are a system, a device, a computer system and a computer program product all for detecting an infringement by a vehicle operator. The device may comprise one or more flash for illuminating the vehicle or a part thereof with light at a narrow band and one or more camera comprising a narrow band filter that lets through only the wavelengths of light produced by the one or more flash.
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公开(公告)号:US12054066B2
公开(公告)日:2024-08-06
申请号:US18348272
申请日:2023-07-06
Applicant: Volta Charging, LLC
Inventor: Ramsey Rolland Meyer
CPC classification number: B60L53/65 , B60L53/66 , G06N3/08 , G06V20/10 , G06V2201/08 , G06V2201/10
Abstract: The disclosed embodiments provide a method performed at a computer system that is in communication with an electric vehicle charging station (EVCS). The EVCS includes a camera for obtaining images in a region proximal to the EVCS. The method includes capturing, using the camera, a plurality of images of electric vehicles, each image in the plurality of images being an image of a respective electric vehicle. The method further includes, for each respective image of the plurality of images of electric vehicles: determining, without user intervention, a characteristic of the respective electric vehicle; and tagging, without user intervention, the respective image with the characteristic of the respective electric vehicle. The method further includes training a first machine learning algorithm to identify the characteristic of other electric vehicles using the tagged plurality of images.
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公开(公告)号:US20240249493A1
公开(公告)日:2024-07-25
申请号:US18156604
申请日:2023-01-19
Applicant: Verizon Patent and Licensing Inc.
Inventor: Leonardo TACCARI , Francesco SAMBO , Douglas COIMBRA DE ANDRADE
IPC: G06V10/22 , G06V10/764 , G06V20/40 , G06V20/56 , G06V20/58
CPC classification number: G06V10/225 , G06V10/764 , G06V20/41 , G06V20/58 , G06V20/588 , G06V2201/08
Abstract: In some implementations, a video system may capture, from a camera mounted to a vehicle, a video of a portion of a road on which the vehicle is traveling. The video system may detect, in the video, a driving lane associated with the road on which the vehicle is traveling. The video system may detect, in the video, multiple other vehicles within the driving lane. The video system may determine, for each of the multiple other vehicles within the driving lane, a bounding box that substantially surrounds an image of the other vehicle, resulting in a plurality of bounding boxes. The video system may determine a region in the video corresponding to an area to be driven by the vehicle based on the plurality of bounding boxes.
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公开(公告)号:US12039864B2
公开(公告)日:2024-07-16
申请号:US17730961
申请日:2022-04-27
Inventor: Yuting Du , Xu Dai , Mengyao Sun , Shilei Wen
CPC classification number: G08G1/0175 , G06T3/40 , G06T7/70 , G06V10/82 , G06V20/46 , G06V20/54 , H04N23/635 , G06T2207/10016 , G06T2207/30236 , G06T2207/30252 , G06V2201/08
Abstract: A method of recognizing illegal parking of a vehicle, a device, and a storage medium, which relate to the field of artificial intelligence, and in particular to the fields of deep learning, cloud computing, computer vision, etc. The method includes: obtaining a video image collected by an electronic device; recognizing a parking area of the vehicle in the video image; determining a shooting angle used by the electronic device for collecting the video image; determining an illegal parking area in the video image based on the shooting angle; and recognizing whether the vehicle is illegally parked or not based on the parking area of the vehicle and the illegal parking area.
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公开(公告)号:US12038320B2
公开(公告)日:2024-07-16
申请号:US17556928
申请日:2021-12-20
Applicant: NEC Laboratories America, Inc.
Inventor: Shaobo Han , Yuheng Chen , Ming-Fang Huang , Tingfeng Li
CPC classification number: G01H9/004 , B60W30/18 , G06V10/14 , G06V10/82 , G06V20/52 , H04B10/2537 , B60W2420/406 , G06V2201/08
Abstract: A fiber optic sensing technology for vehicle run-off-road incident automatic detection by an indicator of sonic alert pattern (SNAP) vibration patterns. A machine learning method is employed and trained and evaluated against a variety of heterogeneous factors using controlled experiments, demonstrating applicability for future field deployment. Extracted events resulting from operation of our system may be advantageously incorporated into existing management systems for intelligent transportation and smart city applications, facilitating real-time alleviation of traffic congestion and/or providing a quick response rescue and clearance operation.
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公开(公告)号:US20240233398A1
公开(公告)日:2024-07-11
申请号:US18405823
申请日:2024-01-05
Applicant: AUTOBRAINS TECHNOLOGIES LTD
Inventor: Adam HAREL , Karina Odinaev , Igal Raichelgauz , Tal Glantz , Shay Leizerovitch
CPC classification number: G06V20/58 , G06T3/60 , G06T7/70 , G06V10/74 , G06V10/774 , G06V10/82 , G06T2207/20081 , G06T2207/20084 , G06T2207/30244 , G06T2207/30261 , G06V2201/08
Abstract: A method for motorcycle roll angle robust object detection, the method includes receiving, by a processing circuit, an image of an environment of the vehicle, wherein the image was obtained by a camera associated with a motorcycle; and generating, by the processing circuit, a signature of the image; finding, by the processing circuit, using the generated signature, a matching concept data structure out of multiple concept data structures; wherein the multiple concept data structure represents images acquired at multiple roll angles of a field of view of the camera; and detecting, by the processing circuit, within the image, an object or a scenario that is associated with the matching concept data structure.
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公开(公告)号:US20240233329A1
公开(公告)日:2024-07-11
申请号:US18401852
申请日:2024-01-02
Applicant: Volvo Truck Corporation
Inventor: Robin Karlsson , Hampus Ek
IPC: G06V10/764 , G06V10/98 , G07C5/08
CPC classification number: G06V10/764 , G06V10/993 , G07C5/0808 , G06V2201/08
Abstract: A computer system comprising a processor device configured to obtain at least one image of a vehicle, wherein the at least one image comprises at least one air drag affecting portion of the vehicle affecting the air drag of the vehicle, estimate an air drag of the vehicle comprising the at least one air drag affecting portion using a machine learning algorithm, identify the at least one air drag affecting portion in the at least one image, and to estimate an impact that the at least one air drag affecting portion has on the vehicle's air drag and energy consumption.
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公开(公告)号:US20240233304A9
公开(公告)日:2024-07-11
申请号:US18048649
申请日:2022-10-21
Applicant: Valeo Schalter und Snsoren GmbH
Inventor: Jagdish Bhanushali , Peter Groth
CPC classification number: G06V10/16 , G06T5/005 , G06T7/55 , G06V10/273 , G06V10/774 , G06V10/82 , G06V20/58 , B60R1/22 , G06T2207/20081 , G06T2207/20084 , G06T2207/30252 , G06V2201/08
Abstract: A method for generating an unobstructed bowl view of a vehicle that includes obtaining a plurality of images from a plurality of cameras disposed on the vehicle and determining a plurality of depth fields. The method further includes detecting a plurality of distorted objects in the plurality of images with a first machine-learned model that assigns a class distribution to the detected distorted object and estimating a distance of each distorted object from its associated camera using the plurality of depth fields. The method further includes assigning an object weight to each distorted object in the plurality of distorted objects and removing at least one distorted objects from the plurality of images. The method further includes replacing each of the at least one removed distorted objects with a representative background generated by a second machine-learned model and stitching and projecting the plurality of images to form the unobstructed bowl view.
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公开(公告)号:US20240233048A9
公开(公告)日:2024-07-11
申请号:US18278465
申请日:2022-02-22
Applicant: Komatsu Ltd.
Inventor: Shun Kawamoto , Tsubasa Hasumi , Minami Sugimura , Li Dong , Shota Hirama
CPC classification number: G06Q50/08 , G06T17/00 , G06V20/17 , G06V40/10 , G06V2201/08
Abstract: A construction management system includes a current terrain data creation unit that creates current terrain data of a construction site on which a work machine operates, a detection data acquisition unit that acquires detection data of a detection device that detects the construction site, a reflection unit that generates reflection data in which the detection data is reflected in the current terrain data, and an output unit that outputs the reflection data on a display device.
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公开(公告)号:US20240212359A1
公开(公告)日:2024-06-27
申请号:US18087388
申请日:2022-12-22
Applicant: HERE Global B.V.
Inventor: Amarnath Nayak , Bruce Bernhardt
CPC classification number: G06V20/58 , G01C21/3469 , G06T7/10 , G06V10/26 , G06V10/82 , G06T2207/20081 , G06T2207/20084 , G06T2207/20132 , G06T2207/30236 , G06T2207/30242 , G06T2207/30252 , G06V2201/08
Abstract: Systems and methods are described for the vehicle emission measurement. An example method may include receiving a plurality of images from a first vehicle traveling on a section of roadway, determining a quantity of surrounding vehicles from the plurality of images, determining a cropped image of at least one of the surrounding vehicles from the plurality of images, identifying a model of the at least one of the surrounding vehicles from the cropped image, and calculating an emission measurement factor for the section of roadway based on at least the quantity of surrounding vehicles for the at least one of the surrounding vehicles.
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