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公开(公告)号：US20220207776A1
公开(公告)日：2022-06-30
申请号：US17604288
申请日：2020-03-05
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY , PENG CHENG LABORATORY
Inventor： Wei ZHONG , Hong ZHANG , Haojie LI , Zhihui WANG , Risheng LIU , Xin FAN , Zhongxuan LUO , Shengquan LI
Abstract: A disparity image fusion method for multiband stereo cameras belongs to the field of image processing and computer vision. The method obtains pixel disparity confidence information by using the intermediate output of binocular disparity estimation. The confidence information can be used to judge the disparity credibility of the position and assist disparity fusion. The confidence acquisition process makes full use of the intermediate output of calculation, and can be conveniently embedded into the traditional disparity estimation process, with high calculation efficiency and simple and easy operation. In the disparity image fusion method for multiband stereo cameras proposed by the method, the disparity diagrams participating in the fusion are obtained according to the binocular images of the corresponding bands, which makes full use of the information of each band and simultaneously avoiding introducing uncertainty and errors.
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公开(公告)号：US20220092809A1
公开(公告)日：2022-03-24
申请号：US17604239
申请日：2020-03-05
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY , PENG CHENG LABORATORY
Inventor： Wei ZHONG , Hong ZHANG , Haojie LI , Zhihui WANG , Risheng LIU , Xin FAN , Zhongxuan LUO , Shengquan LI
Abstract: The present invention discloses a disparity estimation method for weakly supervised trusted cost propagation, which utilizes a deep learning method to optimize the initial cost obtained by the traditional method. By combining and making full use of respective advantages, the problems of false matching and difficult matching of untextured regions in the traditional method are solved, and the method for weakly supervised trusted cost propagation avoids the problem of data label dependency of the deep learning method.
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公开(公告)号：US20220215569A1
公开(公告)日：2022-07-07
申请号：US17603856
申请日：2020-03-05
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY , PENG CHENG LABORATORY
Inventor： Wei ZHONG , Hong ZHANG , Haojie LI , Zhihui WANG , Risheng LIU , Xin FAN , Zhongxuan LUO , Shengquan LI
Abstract: The present invention belongs to the field of image processing and computer vision, and discloses an acceleration method of depth estimation for multiband stereo cameras. In the process of depth estimation, during binocular stereo matching in each band, through compression of matched images, on one hand, disparity equipotential errors caused by binocular image correction can be offset to make the matching more accurate, and on the other hand, calculation overhead is reduced. In addition, before cost aggregation, cost diagrams are transversely compressed and sparsely matched, thereby reducing the calculation overhead again. Disparity diagrams obtained under different modes are fused to obtain all-weather, more complete and more accurate depth information.
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Patent Agency Ranking
公开(公告)号：US20220198694A1
公开(公告)日：2022-06-23
申请号：US17604588
申请日：2020-03-05
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY , PENG CHENG LABORATORY
Inventor： Wei ZHONG , Hong ZHANG , Haojie LI , Zhihui WANG , Risheng LIU , Xin FAN , Zhongxuan LUO , Shengquan LI
Abstract: The present invention discloses a disparity estimation optimization method based on upsampling and exact rematching, which conducts exact rematching within a small range in an optimized network, improves previous upsampling methods such as neighbor interpolation and bilinear interpolation for disparity maps or cost maps, and works out a propagation-based upsampling method by the way of network so that accurate disparity values can be better restored from disparity maps in the upsampling process.
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公开(公告)号：US20200273190A1
公开(公告)日：2020-08-27
申请号：US16650331
申请日：2019-01-07
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY
Inventor： Xinchen YE , Wei ZHONG , Zhihui WANG , Haojie LI , Lin LIN , Xin FAN , Zhongxuan LUO
Abstract: The present invention provides a method of dense 3D scene reconstruction based on monocular camera and belongs to the technical field of image processing and computer vision, which builds the reconstruction strategy with fusion of traditional geometry-based depth computation and convolutional neural network (CNN) based depth prediction, and formulates depth reconstruction model solved by efficient algorithm to obtain high-quality dense depth map. The system is easy to construct because of its low requirement for hardware resources and achieves dense reconstruction only depending on ubiquitous monocular cameras. Camera tracking of feature-based SLAM provides accurate pose estimation, while depth reconstruction model with fusion of sparse depth points and CNN-inferred depth achieves dense depth estimation and 3D scene reconstruction; The use of fast solver in depth reconstruction avoids solving inversion of large-scale sparse matrix, which improves running speed of the algorithm and ensures the real-time dense 3D scene reconstruction based on monocular camera.
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公开(公告)号：US20220028043A1
公开(公告)日：2022-01-27
申请号：US17284394
申请日：2020-03-05
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY
Inventor： Wei ZHONG , Haojie LI , Boqian LIU , Zhihui WANG , Risheng LIU , Zhongxuan LUO , Xin FAN
Abstract: A multispectral camera dynamic stereo calibration algorithm is based on saliency features. The joint self-calibration method comprises the following steps: step 1: conducting de-distortion and binocular correction on an original image according to internal parameters and original external parameters of an infrared camera and a visible light camera. Step 2: Detecting the saliency of the infrared image and the visible light image respectively based on a histogram contrast method. Step 3: Extracting feature points on the infrared image and the visible light image. Step 4: Matching the feature points extracted in the previous step. Step 5: judging a feature point coverage area. Step 6: correcting the calibration result. The present invention solves the change of a positional relationship between an infrared camera and a visible light camera due to factors such as temperature, humidity and vibration.
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7.发明申请公开(公告)号：US20220036589A1
公开(公告)日：2022-02-03
申请号：US17279461
申请日：2020-03-05
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY
Inventor： Wei ZHONG , Boqian LIU , Haojie LI , Zhihui WANG , Risheng LIU , Xin FAN , Zhongxuan LUO
IPC: G06T7/80 , H04N13/239 , H04N13/156 , H04N13/25 , G06T7/13
Abstract: The present invention discloses a multispectral camera external parameter self-calibration algorithm based on edge features, and belongs to the field of image processing and computer vision. Because a visible light camera and an infrared camera belong to different modes, fewer satisfactory point pairs are obtained by directly extracting and matching feature points. In order to solve the problem, the method starts from the edge features, and finds an optimal corresponding position of an infrared image on a visible light image through edge extraction and matching. In this way, a search range is reduced and the number of the satisfactory matched point pairs is increased, thereby more effectively conducting joint self-calibration on the infrared camera and the visible light camera. The operation is simple and results are accurate.
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公开(公告)号：US20210312197A1
公开(公告)日：2021-10-07
申请号：US17280745
申请日：2020-03-05
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY
Inventor： Wei ZHONG , Shenglun CHEN , Haojie LI , Zhihui WANG , Risheng LIU , Xin FAN , Zhongxuan LUO
Abstract: The present invention discloses a grid map obstacle detection method fusing probability and height information, and belongs to the field of image processing and computer vision. A high-performance computing platform is constructed by using a GPU, and a high-performance solving algorithm is constructed to obtain obstacle information in a map. The system is easy to construct, the program is simple, and is easy to implement. The positions of obstacles are acquired in a multi-layer grid map by fusing probability and height information, so the robustness is high and the precision is high.
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