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

IPC: G06T7/55 ,  G06T5/00 ,  G06K9/62 ,  G06N20/00 ,  G06T5/20

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.

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

IPC: G06T7/579 ,  G06T17/00 ,  G06T7/70 ,  G06T7/246

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.