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公开(公告)号：US20190180115A1
公开(公告)日：2019-06-13
申请号：US15837276
申请日：2017-12-11
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Guangyu J. Zou
Abstract: Systems and method are provided for controlling a vehicle. In one embodiment, a method of controlling a vehicle, includes receiving, via at least one processor, image data from each of plural cameras mounted on the vehicle. The method includes assembling, via the at least one processor, the image data from each of the plural cameras to form assembled image data. The method includes classifying and localizing lane features using an artificial neural network based on the assembled image data, to produce classified and localized lane data. The method includes performing, via the at least one processor, a data fusion process based on the classified and localized lane data, thereby producing fused lane feature data. The method includes controlling, via the at least one processor, the vehicle based, in part, on the fused lane feature data.
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公开(公告)号：US20230068046A1
公开(公告)日：2023-03-02
申请号：US17410211
申请日：2021-08-24
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Lawrence A. Bush , Guangyu J. Zou , Aravindhan Mani , Upali P. Mudalige
Abstract: Systems and methods of detecting a traffic object outside of a vehicle and controlling the vehicle. The systems and methods receive perception data from a sensor system included in the vehicle, determine a focused Region Of Interest (ROI) in the perception data, scale the perception data of the at least one focused ROI, process the scaled perception data of the focused ROI using a neural network (NN)-based traffic object detection algorithm to provide traffic object detection data, and control at least one vehicle feature based, in part, on the traffic object detection data.
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公开(公告)号：US10893183B1
公开(公告)日：2021-01-12
申请号：US16686407
申请日：2019-11-18
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Guangyu J. Zou , Shuqing Zeng , Upali P. Mudalige
IPC: H04N5/225 , B60R11/04 , G01S17/931
Abstract: An attention-based imaging system is described, including a camera that can adjust its field of view (FOV) and resolution and a control routine that can determine one or more regions of interest (ROI) within the FOV to prioritize camera resources. The camera includes an image sensor, an internal lens, a steerable mirror, an external lens, and a controller. The external lens is disposed to monitor a viewable region, and the steerable mirror is interposed between the internal lenses and the external lenses. The steerable mirrors are arranged to project the viewable region from the external lens onto the image sensor via the internal lens. The steerable mirror modifies the viewable region that is projected onto the image sensor and controls the image sensor to capture an image. The associated control routine can be deployed either inside the camera or in a separate external processor.
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Patent Agency Ranking
公开(公告)号：US10528054B2
公开(公告)日：2020-01-07
申请号：US15844732
申请日：2017-12-18
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Guangyu J. Zou
Abstract: Systems and methods are provided for detecting features from multi-modal image-like data representations. The system includes a wavelet transformer configured to, via at least one processor, receive image data and to wavelet transform the image data, thereby providing decomposed image data divided into frequency sub-bands. The system further includes an artificial neural network configured to receive and process at least one sub-band of the decomposed image data to detect image features based thereon, the artificial neural network configured to output the detected image features.
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公开(公告)号：US10402670B2
公开(公告)日：2019-09-03
申请号：US15487753
申请日：2017-04-14
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Guangyu J. Zou , Upali P. Mudalige , Jinsong Wang
Abstract: Techniques for road scene primitive detection using a vehicle camera system are disclosed. In one example implementation, a computer-implemented method includes receiving, by a processing device having at least two parallel processing cores, at least one image from a camera associated with a vehicle on a road. The processing device generates a plurality of views from the at least one image that include a feature primitive. The feature primitive is indicative of a vehicle or other road scene entities of interest. Using each of the parallel processing cores, a set of primitives are identified from one or more of the plurality of views. The feature primitives are identified using one or more of machine learning and classic computer vision techniques. The processing device outputs, based on the plurality of views, result primitives based on the plurality of identified primitives from multiple views based on the plurality of identified entities.
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公开(公告)号：US20190204842A1
公开(公告)日：2019-07-04
申请号：US15859857
申请日：2018-01-02
Applicant: GM Global Technology Operations LLC
Inventor： Sayyed Rouhollah Jafari Tafti , Guangyu J. Zou , Marcus J. Huber , Upali P. Mudalige
CPC classification number: G05D1/0221 , G05D1/0088 , G06N3/04 , G06N3/08
Abstract: A vehicle, system and method of autonomous navigation of the vehicle. A reference trajectory for navigating a training traffic scenario along a road section is received at a processor of the vehicle. The processor determines a coefficient for a cost function associated with a candidate trajectory that simulates the reference trajectory. The determined coefficient is provided to a neural network to train the neural network. The trained neural network generates a navigation trajectory for navigating the vehicle using a cost coefficient determined by the neural network. The vehicle is navigated along the road section using the navigation trajectory.
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公开(公告)号：US20190187718A1
公开(公告)日：2019-06-20
申请号：US15844732
申请日：2017-12-18
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Guangyu J. Zou
CPC classification number: G05D1/0231 , G06K9/00798 , G06K9/66 , G06N3/02 , G06N3/0454 , G06N3/082 , G06T1/20 , G06T5/20
Abstract: Systems and methods are provided for detecting features from multi-modal image-like data representations. The system includes a wavelet transformer configured to, via at least one processor, receive image data and to wavelet transform the image data, thereby providing decomposed image data divided into frequency sub-bands. The system further includes an artificial neural network configured to receive and process at least one sub-band of the decomposed image data to detect image features based thereon, the artificial neural network configured to output the detected image features.
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公开(公告)号：US20170300767A1
公开(公告)日：2017-10-19
申请号：US15487753
申请日：2017-04-14
Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Inventor： Guangyu J. Zou , Upali P. Mudalige , Jinsong Wang
CPC classification number: G06K9/00986 , B60R1/00 , B60R2300/102 , B60R2300/105 , B60R2300/607 , B60R2300/8033 , B60R2300/8093 , G06K9/00791 , G06K9/4619 , G06K9/4628 , G06K9/6269 , H04N5/23293 , H04N5/247
Abstract: Techniques for road scene primitive detection using a vehicle camera system are disclosed. In one example implementation, a computer-implemented method includes receiving, by a processing device having at least two parallel processing cores, at least one image from a camera associated with a vehicle on a road. The processing device generates a plurality of views from the at least one image that include a feature primitive. The feature primitive is indicative of a vehicle or other road scene entities of interest. Using each of the parallel processing cores, a set of primitives are identified from one or more of the plurality of views. The feature primitives are identified using one or more of machine learning and classic computer vision techniques. The processing device outputs, based on the plurality of views, result primitives based on the plurality of identified primitives from multiple views based on the plurality of identified entities.
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