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公开(公告)号：US11694308B2
公开(公告)日：2023-07-04
申请号：US17308911
申请日：2021-05-05
申请人： TUSIMPLE, INC.
发明人： Pengfei Chen , Nan Yu , Naiyan Wang , Xiaodi Hou
CPC分类号： G06T5/002 , B60W40/02 , G06T5/004 , G06T5/009 , H04N25/13 , B60W2420/42 , G06T2207/10024
摘要： Disclosed are devices, systems and methods for processing an image. In one aspect a method includes receiving an image from a sensor array including an x-y array of pixels, each pixel in the x-y array of pixels having a value selected from one of three primary colors, based on a corresponding x-y value in a mask pattern. The method may further include generating a preprocessed image by performing preprocessing on the image. The method may further include performing perception on the preprocessed image to determine one or more outlines of physical objects.
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公开(公告)号：US11010874B2
公开(公告)日：2021-05-18
申请号：US16381707
申请日：2019-04-11
申请人： TuSimple, Inc.
发明人： Pengfei Chen , Nan Yu , Naiyan Wang , Xiaodi Hou
摘要： Disclosed are devices, systems and methods for processing an image. In one aspect a method includes receiving an image from a sensor array including an x-y array of pixels, each pixel in the x-y array of pixels having a value selected from one of three primary colors, based on a corresponding x-y value in a mask pattern. The method may further include generating a preprocessed image by performing preprocessing on the image. The method may further include performing perception on the preprocessed image to determine one or more outlines of physical objects.
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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
申请人： TuSimple, Inc.
发明人： Hongkai Yu , Zhipeng Yan , Panqu Wang , Pengfei Chen
摘要： 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
申请人： TUSIMPLE, INC.
发明人： Zhipeng Yan , Lingting Ge , Pengfei Chen , Panqu Wang
摘要： 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：US10685244B2
公开(公告)日：2020-06-16
申请号：US15906561
申请日：2018-02-27
申请人： TuSimple, Inc.
发明人： Lingting Ge , Pengfei Chen , Panqu Wang
摘要： A system and method for online real-time multi-object tracking is disclosed. A particular embodiment can be configured to: receive image frame data from at least one camera associated with an autonomous vehicle; generate similarity data corresponding to a similarity between object data in a previous image frame compared with object detection results from a current image frame; use the similarity data to generate data association results corresponding to a best matching between the object data in the previous image frame and the object detection results from the current image frame; cause state transitions in finite state machines for each object according to the data association results; and provide as an output object tracking output data corresponding to the states of the finite state machines for each object.
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公开(公告)号：US11830205B2
公开(公告)日：2023-11-28
申请号：US17656415
申请日：2022-03-24
申请人： TUSIMPLE, INC.
发明人： Lingting Ge , Pengfei Chen , Panqu Wang
IPC分类号： G06T7/00 , G06T7/277 , G06N3/08 , G06N3/04 , G06T7/246 , G06T7/73 , G06V20/58 , G06V10/764 , G06V10/82 , G06V10/62
CPC分类号： G06T7/277 , G06N3/04 , G06N3/08 , G06T7/248 , G06T7/74 , G06V10/764 , G06V10/82 , G06V20/58 , B60Y2400/3015 , G06T2207/30248 , G06V10/62
摘要： A system and method for online real-time multi-object tracking is disclosed. A particular embodiment can be configured to: receive image frame data from at least one camera associated with an autonomous vehicle; generate similarity data corresponding to a similarity between object data in a previous image frame compared with object detection results from a current image frame; use the similarity data to generate data association results corresponding to a best matching between the object data in the previous image frame and the object detection results from the current image frame; cause state transitions in finite state machines for each object according to the data association results; and provide as an output object tracking output data corresponding to the states of the finite state machines for each object.
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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
申请人： TuSimple, Inc.
发明人： Hongkai Yu , Zhipeng Yan , Panqu Wang , Pengfei Chen
IPC分类号： B60W30/095 , G06V10/25 , G06V10/44 , G06V20/56 , G06V20/58 , G06F18/24 , G06F18/214 , G06F18/2413 , G06V10/774 , G06V10/70 , G05D1/02
CPC分类号： B60W30/0956 , G06F18/2155 , G06F18/24 , G06F18/2413 , G06V10/25 , G06V10/44 , G06V10/7753 , G06V10/87 , G06V20/56 , G06V20/58 , G05D1/0221
摘要： 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：US11501513B2
公开(公告)日：2022-11-15
申请号：US16855951
申请日：2020-04-22
申请人： TUSIMPLE, INC.
发明人： Panqu Wang , Pengfei Chen
摘要： A system and method for vehicle wheel detection is disclosed. A particular embodiment can be configured to: receive training image data from a training image data collection system; obtain ground truth data corresponding to the training image data; perform a training phase to train one or more classifiers for processing images of the training image data to detect vehicle wheel objects in the images of the training image data; receive operational image data from an image data collection system associated with an autonomous vehicle; and perform an operational phase including applying the trained one or more classifiers to extract vehicle wheel objects from the operational image data and produce vehicle wheel object data.
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9.发明授权公开(公告)号：US10962979B2
公开(公告)日：2021-03-30
申请号：US15721797
申请日：2017-09-30
申请人： TuSimple, Inc.
发明人： Xiangchen Zhao , Tian Li , Panqu Wang , Pengfei Chen
摘要： A system and method for multitask processing for autonomous vehicle computation and control includes: receiving training image data from a training image data collection system; performing a training phase to train a plurality of tasks associated with features of the training image data, the training phase including extracting common features from the training image data, causing the plurality of tasks to generate task-specific predictions based on the training image data, determining a bias between the task-specific prediction for each task and corresponding task-specific ground truth data, and adjusting parameters of each of the plurality of tasks to cause the bias to meet a pre-defined confidence level; receiving image data from an image data collection system associated with an autonomous vehicle; and performing an operational phase including extracting common features from the image data, causing the plurality of trained tasks to concurrently generate task-specific predictions based on the image data.
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10.发明授权公开(公告)号：US10528851B2
公开(公告)日：2020-01-07
申请号：US15822467
申请日：2017-11-27
申请人： TuSimple
发明人： Ligeng Zhu , Panqu Wang , Pengfei Chen
摘要： A system and method for drivable road surface representation generation using multimodal sensor data are disclosed. A particular embodiment includes: receiving image data from an image generating device mounted on a vehicle and receiving three dimensional (3D) point cloud data from a distance measuring device mounted on the vehicle; projecting the 3D point cloud data onto the 2D image data to produce mapped image and point cloud data; performing post-processing operations on the mapped image and point cloud data; and performing a smoothing operation on the processed mapped image and point cloud data to produce a drivable road surface map or representation.
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