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公开(公告)号：US11935210B2
公开(公告)日：2024-03-19
申请号：US17018627
申请日：2020-09-11
Applicant: TUSIMPLE, INC.
Inventor： Zhipeng Yan , Pengfei Chen , Panqu Wang
CPC classification number: G06T3/0018 , G05D1/0246 , G06T5/006 , G06T5/20 , G06T2207/30252
Abstract: A system and method for fisheye image processing can be configured to: receive fisheye image data from at least one fisheye lens camera associated with an autonomous vehicle, the fisheye image data representing at least one fisheye image frame; partition the fisheye image frame into a plurality of image portions representing portions of the fisheye image frame; warp each of the plurality of image portions to map an arc of a camera projected view into a line corresponding to a mapped target view, the mapped target view being generally orthogonal to a line between a camera center and a center of the arc of the camera projected view; combine the plurality of warped image portions to form a combined resulting fisheye image data set representing recovered or distortion-reduced fisheye image data corresponding to the fisheye image frame; generate auto-calibration data representing a correspondence between pixels in the at least one fisheye image frame and corresponding pixels in the combined resulting fisheye image data set; and provide the combined resulting fisheye image data set as an output for other autonomous vehicle subsystems.
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公开(公告)号：US10783381B2
公开(公告)日：2020-09-22
申请号：US16416248
申请日：2019-05-19
Applicant: TuSimple, Inc.
Inventor： Hongkai Yu , Zhipeng Yan , Panqu Wang , Pengfei Chen
Abstract: A system and method for vehicle occlusion detection is disclosed. A particular embodiment includes: receiving training image data from a training image data collection system; obtaining ground truth data corresponding to the training image data; performing a training phase to train a plurality of classifiers, a first classifier being trained for processing static images of the training image data, a second classifier being trained for processing image sequences of the training image data; receiving image data from an image data collection system associated with an autonomous vehicle; and performing an operational phase including performing feature extraction on the image data, determining a presence of an extracted feature instance in multiple image frames of the image data by tracing the extracted feature instance back to a previous plurality of N frames relative to a current frame, applying the first trained classifier to the extracted feature instance if the extracted feature instance cannot be determined to be present in multiple image frames of the image data, and applying the second trained classifier to the extracted feature instance if the extracted feature instance can be determined to be present in multiple image frames of the image data.
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公开(公告)号：US20200265243A1
公开(公告)日：2020-08-20
申请号：US16865800
申请日：2020-05-04
Applicant: TUSIMPLE, INC.
Inventor： Zhipeng Yan , Lingting Ge , Pengfei Chen , Panqu Wang
Abstract: A system and method for lateral vehicle detection is disclosed. A particular embodiment can be configured to: receive lateral image data from at least one laterally-facing camera associated with an autonomous vehicle; warp the lateral image data based on a line parallel to a side of the autonomous vehicle; perform object extraction on the warped lateral image data to identify extracted objects in the warped lateral image data; and apply bounding boxes around the extracted objects.
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公开(公告)号：US12243428B2
公开(公告)日：2025-03-04
申请号：US18121117
申请日：2023-03-14
Applicant: TUSIMPLE, INC.
Inventor： Zhipeng Yan , Lingting Ge , Pengfei Chen , Panqu Wang
IPC: G08G1/16 , G05D1/00 , G06T3/18 , G06T7/73 , G06V10/44 , G06V10/75 , G06V20/56 , G06V20/58 , G08G1/04
Abstract: A system and method for lateral vehicle detection is disclosed. A particular embodiment can be configured to: receive lateral image data from at least one laterally-facing camera associated with an autonomous vehicle; warp the lateral image data based on a line parallel to a side of the autonomous vehicle; perform object extraction on the warped lateral image data to identify extracted objects in the warped lateral image data; and apply bounding boxes around the extracted objects.
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公开(公告)号：US11745736B2
公开(公告)日：2023-09-05
申请号：US17006283
申请日：2020-08-28
Applicant: TuSimple, Inc.
Inventor： Hongkai Yu , Zhipeng Yan , Panqu Wang , Pengfei Chen
IPC: B60W30/095 , G06V10/25 , G06V10/44 , G06V20/56 , G06V20/58 , G06F18/24 , G06F18/214 , G06F18/2413 , G06V10/774 , G06V10/70 , G05D1/02
CPC classification number: B60W30/0956 , G06F18/2155 , G06F18/24 , G06F18/2413 , G06V10/25 , G06V10/44 , G06V10/7753 , G06V10/87 , G06V20/56 , G06V20/58 , G05D1/0221
Abstract: A system and method for vehicle occlusion detection is disclosed. A particular embodiment includes: receiving training image data from a training image data collection system; obtaining ground truth data corresponding to the training image data; performing a training phase to train a plurality of classifiers, a first classifier being trained for processing static images of the training image data, a second classifier being trained for processing image sequences of the training image data; receiving image data from an image data collection system associated with an autonomous vehicle; and performing an operational phase including performing feature extraction on the image data, determining a presence of an extracted feature instance in multiple image frames of the image data by tracing the extracted feature instance back to a previous plurality of N frames relative to a current frame, applying the first trained classifier to the extracted feature instance if the extracted feature instance cannot be determined to be present in multiple image frames of the image data, and applying the second trained classifier to the extracted feature instance if the extracted feature instance can be determined to be present in multiple image frames of the image data.
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Patent Agency Ranking
公开(公告)号：US11104334B2
公开(公告)日：2021-08-31
申请号：US15994138
申请日：2018-05-31
Applicant: TuSimple, Inc.
Inventor： Zhipeng Yan , Mingdong Wang , Siyuan Liu , Xiaodi Hou
Abstract: A system and method for proximate vehicle intention prediction for autonomous vehicles are disclosed. A particular embodiment is configured to: receive perception data associated with a host vehicle; extract features from the perception data to detect a proximate vehicle in the vicinity of the host vehicle; generate a trajectory of the detected proximate vehicle based on the perception data; use a trained intention prediction model to generate a predicted intention of the detected proximate vehicle based on the perception data and the trajectory of the detected proximate vehicle; use the predicted intention of the detected proximate vehicle to generate a predicted trajectory of the detected proximate vehicle; and output the predicted intention and predicted trajectory for the detected proximate vehicle to another subsystem.
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公开(公告)号：US11074462B2
公开(公告)日：2021-07-27
申请号：US16865800
申请日：2020-05-04
Applicant: TUSIMPLE, INC.
Inventor： Zhipeng Yan , Lingting Ge , Pengfei Chen , Panqu Wang
IPC: G05D1/00 , G05D1/02 , G06K9/00 , G06K9/62 , G06T3/00 , G06T3/40 , G08G1/04 , G06G1/16 , H04N7/18
Abstract: A system and method for lateral vehicle detection is disclosed. A particular embodiment can be configured to: receive lateral image data from at least one laterally-facing camera associated with an autonomous vehicle; warp the lateral image data based on a line parallel to a side of the autonomous vehicle; perform object extraction on the warped lateral image data to identify extracted objects in the warped lateral image data; and apply bounding boxes around the extracted objects.
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公开(公告)号：US10762635B2
公开(公告)日：2020-09-01
申请号：US15623323
申请日：2017-06-14
Applicant: TuSimple, Inc.
Inventor： Zhipeng Yan , Zehua Huang , Pengfei Chen , Panqu Wang
Abstract: A system and method for actively selecting and labeling images for semantic segmentation are disclosed. A particular embodiment includes: receiving image data from an image generating device; performing semantic segmentation or other object detection on the received image data to identify and label objects in the image data and produce semantic label image data; determining the quality of the semantic label image data based on prediction probabilities associated with regions or portions of the image; and identifying a region or portion of the image for manual labeling if an associated prediction probability is below a pre-determined threshold.
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公开(公告)号：US10685239B2
公开(公告)日：2020-06-16
申请号：US15924249
申请日：2018-03-18
Applicant: TuSimple, Inc.
Inventor： Zhipeng Yan , Lingting Ge , Pengfei Chen , Panqu Wang
Abstract: A system and method for lateral vehicle detection is disclosed. A particular embodiment can be configured to: receive lateral image data from at least one laterally-facing camera associated with an autonomous vehicle; warp the lateral image data based on a line parallel to a side of the autonomous vehicle; perform object extraction on the warped lateral image data to identify extracted objects in the warped lateral image data; and apply bounding boxes around the extracted objects.
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公开(公告)号：US12190465B2
公开(公告)日：2025-01-07
申请号：US18437734
申请日：2024-02-09
Applicant: TUSIMPLE, INC.
Inventor： Zhipeng Yan , Pengfei Chen , Panqu Wang
Abstract: A system and method for fisheye image processing can be configured to: receive fisheye image data from at least one fisheye lens camera associated with an autonomous vehicle, the fisheye image data representing at least one fisheye image frame; partition the fisheye image frame into a plurality of image portions representing portions of the fisheye image frame; warp each of the plurality of image portions to map an arc of a camera projected view into a line corresponding to a mapped target view, the mapped target view being generally orthogonal to a line between a camera center and a center of the arc of the camera projected view; combine the plurality of warped image portions to form a combined resulting fisheye image data set representing recovered or distortion-reduced fisheye image data corresponding to the fisheye image frame; generate auto-calibration data representing a correspondence between pixels in the at least one fisheye image frame and corresponding pixels in the combined resulting fisheye image data set; and provide the combined resulting fisheye image data set as an output for other autonomous vehicle subsystems.
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