The Experts below are selected from a list of 26766 Experts worldwide ranked by ideXlab platform
Ming Gong - One of the best experts on this subject based on the ideXlab platform.
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multi camera Stereo Vision based on weights
The Journal of Thoracic and Cardiovascular Surgery, 2020Co-Authors: Songlin Bi, Yonggang Gu, Chao Zhai, Zhihong Zhang, Ming GongAbstract:The improvement of measurement accuracy has always been a hot topic in visual measurement. The multi-camera Stereo Vision, which is composed of more than two cameras, provides more image information, stronger interference capability and higher 3D reconstruction accuracy than binocular Vision, has been widely used. The imaging quality, camera calibration accuracy and Vision system structure parameters of different cameras may be different. However, in the traditional multicamera Stereo Vision, the contribution of each camera to the reconstruction results is the same, which may lead the reduction of the reconstruction accuracy. In this paper, multi-camera Stereo Vision based on weights is proposed to reduce the impact of cameras with large errors, eventually, the measurement accuracy is improved. The error characteristics are analyzed comprehensively, and the error model is established to calculate weights, then the weighted least square method is used for 3D reconstruction. The feasibility of the proposed method is verified by the trinocular Vision 3D reconstruction experiment. Compared with the traditional 3D reconstruction method based on least square method, the accuracy is improved by about 3%.
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I2MTC - Multi-camera Stereo Vision based on weights
The Journal of Thoracic and Cardiovascular Surgery, 2020Co-Authors: Zhihong Zhang, Chao Zhai, Honghong Liu, Ming GongAbstract:The improvement of measurement accuracy has always been a hot topic in visual measurement. The multi-camera Stereo Vision, which is composed of more than two cameras, provides more image information, stronger interference capability and higher 3D reconstruction accuracy than binocular Vision, has been widely used. The imaging quality, camera calibration accuracy and Vision system structure parameters of different cameras may be different. However, in the traditional multicamera Stereo Vision, the contribution of each camera to the reconstruction results is the same, which may lead the reduction of the reconstruction accuracy. In this paper, multi-camera Stereo Vision based on weights is proposed to reduce the impact of cameras with large errors, eventually, the measurement accuracy is improved. The error characteristics are analyzed comprehensively, and the error model is established to calculate weights, then the weighted least square method is used for 3D reconstruction. The feasibility of the proposed method is verified by the trinocular Vision 3D reconstruction experiment. Compared with the traditional 3D reconstruction method based on least square method, the accuracy is improved by about 3%.
Jae Wook Jeon - One of the best experts on this subject based on the ideXlab platform.
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fpga design and implementation of a real time Stereo Vision system
IEEE Transactions on Circuits and Systems for Video Technology, 2010Co-Authors: Seunghun Jin, Jung Uk Cho, Xuan Dai Pham, Kyoung Mu Lee, Sungkee Park, Munsang Kim, Jae Wook JeonAbstract:Stereo Vision is a well-known ranging method because it resembles the basic mechanism of the human eye. However, the computational complexity and large amount of data access make real-time processing of Stereo Vision challenging because of the inherent instruction cycle delay within conventional computers. In order to solve this problem, the past 20 years of research have focused on the use of dedicated hardware architecture for Stereo Vision. This paper proposes a fully pipelined Stereo Vision system providing a dense disparity image with additional sub-pixel accuracy in real-time. The entire Stereo Vision process, such as rectification, Stereo matching, and post-processing, is realized using a single field programmable gate array (FPGA) without the necessity of any external devices. The hardware implementation is more than 230 times faster when compared to a software program operating on a conventional computer, and shows stronger performance over previous hardware-related studies.
David W. Murray - One of the best experts on this subject based on the ideXlab platform.
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Using real-time Stereo Vision for mobile robot navigation
Autonomous Robots, 2000Co-Authors: David W. Murray, James J. LittleAbstract:This paper describes a working Vision-based mobile robot that navigates and autonomously explores its environment while building occupancy grid maps of the environment. We present a method for reducing Stereo Vision disparity images to two-dimensional map information. Stereo Vision has several attributes that set it apart from other sensors more commonly used for occupancy grid mapping. We discuss these attributes, the errors that some of them create, and how to overcome them. We reduce errors by segmenting disparity images based on continuous disparity surfaces to reject spikes caused by Stereo mismatches. Stereo Vision processing and map updates are done at 5 Hz and the robot moves at speeds of 300 cm/s.
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Stereo Vision based mapping and navigation for mobile robots
Proceedings of International Conference on Robotics and Automation, 1997Co-Authors: David W. Murray, Connor JenningsAbstract:This paper describes a visually guided robot that can plan paths,\nconstruct maps and explore an indoor environment. The robot uses a\ntrinocular Stereo Vision system to produce highly accurate depth images\nat 2 Hz allowing it to safely travel through the environment at 0.5 m/s.\nThe algorithm integrates Stereo Vision, occupancy grid mapping, and\npotential field path planning techniques to form a robust and cohesive\nrobotic system for mapping and navigation. Stereo Vision is shown to be\na viable alternative to active sensing devices such as sonar and laser\nrange finders
James J. Little - One of the best experts on this subject based on the ideXlab platform.
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Using real-time Stereo Vision for mobile robot navigation
Autonomous Robots, 2000Co-Authors: David W. Murray, James J. LittleAbstract:This paper describes a working Vision-based mobile robot that navigates and autonomously explores its environment while building occupancy grid maps of the environment. We present a method for reducing Stereo Vision disparity images to two-dimensional map information. Stereo Vision has several attributes that set it apart from other sensors more commonly used for occupancy grid mapping. We discuss these attributes, the errors that some of them create, and how to overcome them. We reduce errors by segmenting disparity images based on continuous disparity surfaces to reject spikes caused by Stereo mismatches. Stereo Vision processing and map updates are done at 5 Hz and the robot moves at speeds of 300 cm/s.
Seunghun Jin - One of the best experts on this subject based on the ideXlab platform.
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fpga design and implementation of a real time Stereo Vision system
IEEE Transactions on Circuits and Systems for Video Technology, 2010Co-Authors: Seunghun Jin, Jung Uk Cho, Xuan Dai Pham, Kyoung Mu Lee, Sungkee Park, Munsang Kim, Jae Wook JeonAbstract:Stereo Vision is a well-known ranging method because it resembles the basic mechanism of the human eye. However, the computational complexity and large amount of data access make real-time processing of Stereo Vision challenging because of the inherent instruction cycle delay within conventional computers. In order to solve this problem, the past 20 years of research have focused on the use of dedicated hardware architecture for Stereo Vision. This paper proposes a fully pipelined Stereo Vision system providing a dense disparity image with additional sub-pixel accuracy in real-time. The entire Stereo Vision process, such as rectification, Stereo matching, and post-processing, is realized using a single field programmable gate array (FPGA) without the necessity of any external devices. The hardware implementation is more than 230 times faster when compared to a software program operating on a conventional computer, and shows stronger performance over previous hardware-related studies.
