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公开(公告)号：US11967140B2
公开(公告)日：2024-04-23
申请号：US17983129
申请日：2022-11-08
Applicant: TuSimple, Inc.
Inventor： Panqu Wang , Pengfei Chen
IPC: G06V10/82 , G06F18/2413 , G06T7/194 , G06V10/20 , G06V10/44 , G06V10/764 , G06V20/56 , G06V20/58
CPC classification number: G06V10/82 , G06F18/24133 , G06T7/194 , G06V10/255 , G06V10/454 , G06V10/764 , G06V20/56 , G06V20/58 , G06T2207/20081 , G06T2207/30252
Abstract: 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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公开(公告)号：US11610406B2
公开(公告)日：2023-03-21
申请号：US17377206
申请日：2021-07-15
Applicant: TUSIMPLE, INC.
Inventor： Zhipeng Yan , Lingting Ge , Pengfei Chen , Panqu Wang
IPC: G05D1/00 , G05D1/02 , G06T3/00 , G06T3/40 , G06V10/75 , G06V20/56 , G06V20/58 , G08G1/04 , G08G1/16 , 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：US11587304B2
公开(公告)日：2023-02-21
申请号：US16159060
申请日：2018-10-12
Applicant: TuSimple, Inc.
Inventor： Panqu Wang , Pengfei Chen , Zehua Huang
Abstract: A system and method for occluding contour detection using a fully convolutional neural network is disclosed. A particular embodiment includes: receiving an input image; producing a feature map from the input image by semantic segmentation; learning an array of upscaling filters to upscale the feature map into a final dense feature map of a desired size; applying the array of upscaling filters to the feature map to produce contour information of objects and object instances detected in the input image; and applying the contour information onto the input image.
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Patent Agency Ranking
公开(公告)号：US10796402B2
公开(公告)日：2020-10-06
申请号：US16165951
申请日：2018-10-19
Applicant: TuSimple, Inc.
Inventor： Zhipeng Yan , Pengfei Chen , Panqu Wang
Abstract: A system and method for fisheye image processing is disclosed. A particular embodiment 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：US10558864B2
公开(公告)日：2020-02-11
申请号：US15598727
申请日：2017-05-18
Applicant: TuSimple
Inventor： Zehua Huang , Pengfei Chen , Panqu Wang , Ke Xu
Abstract: A system and method for image localization based on semantic segmentation are disclosed. A particular embodiment includes: receiving image data from an image generating device mounted on an autonomous vehicle; 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; identifying extraneous objects in the semantic label image data; removing the extraneous objects from the semantic label image data; comparing the semantic label image data to a baseline semantic label map; and determining a vehicle location of the autonomous vehicle based on information in a matching baseline semantic label map.
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公开(公告)号：US10311312B2
公开(公告)日：2019-06-04
申请号：US15796769
申请日：2017-10-28
Applicant: TuSimple
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：US10303956B2
公开(公告)日：2019-05-28
申请号：US15684791
申请日：2017-08-23
Applicant: TuSimple
Inventor： Zehua Huang , Panqu Wang , Pengfei Chen , Tian Li
Abstract: A system and method for using triplet loss for proposal free instance-wise semantic segmentation for lane detection are disclosed. A particular embodiment includes: receiving image data from an image generating device mounted on an autonomous vehicle; performing a semantic segmentation operation or other object detection on the received image data to identify and label objects in the image data with object category labels on a per-pixel basis and producing corresponding semantic segmentation prediction data; performing a triplet loss calculation operation using the semantic segmentation prediction data to identify different instances of objects with similar object category labels found in the image data; and determining an appropriate vehicle control action for the autonomous vehicle based on the different instances of objects identified in the image data.
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公开(公告)号：US10067509B1
公开(公告)日：2018-09-04
申请号：US15693446
申请日：2017-08-31
Applicant: TuSimple
Inventor： Panqu Wang , Pengfei Chen , Zehua Huang
Abstract: A system method for occluding contour detection using a fully convolutional neural network is disclosed. A particular embodiment includes: receiving an input image; producing a feature map from the input image by semantic segmentation; applying a Dense Upsampling Convolution (DUC) operation on the feature map to produce contour information of objects and object instances detected in the input image; and applying the contour information onto the input image.
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