Results 231 to 240 of about 28,351 (258)
Some of the next articles are maybe not open access.
2000
Multiresolution frameworks have been embraced by the stereo imaging community because of their human-like approach in solving the correspondence problem and reconstructing density maps from binocular images. We describe a method to recover depth information of stereo images based on a multi-channel wavelet transform, where trends in the coefficients ...
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Multiresolution frameworks have been embraced by the stereo imaging community because of their human-like approach in solving the correspondence problem and reconstructing density maps from binocular images. We describe a method to recover depth information of stereo images based on a multi-channel wavelet transform, where trends in the coefficients ...
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Fast Calibrated Stereo Vision for Manipulation
Real-Time Imaging, 1997To make sensors in general, and vision in particular, work for robotic systems we must find ways to extract timely, relevant, accurate information. Building such sensors will require employing any special devices, constraints or calibration that can help us meet these goals. This paper describes in detail issues in developing a calibrated stereo vision
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2009
In the last few years, stereo vision has become a very interesting sensing technology for robotic platforms. Especially for indoor applications, stereo vision brings many advantages. It is passive, so it does not affect its environment, it is small in size, and it is very flexible.
Karina Ambrosch +3 more
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In the last few years, stereo vision has become a very interesting sensing technology for robotic platforms. Especially for indoor applications, stereo vision brings many advantages. It is passive, so it does not affect its environment, it is small in size, and it is very flexible.
Karina Ambrosch +3 more
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1992
We propose a new stereo vision algorithm for finding circles in a scene. In both 2-D images, ellipses are found. The ellipses are matched in order to find circles in 3-D space. The method does not require a special camera alignment, instead both camera matrices must be known.
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We propose a new stereo vision algorithm for finding circles in a scene. In both 2-D images, ellipses are found. The ellipses are matched in order to find circles in 3-D space. The method does not require a special camera alignment, instead both camera matrices must be known.
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Architectures for Stereo Vision
2013Stereo vision is an elementary problem for many computer vision tasks. It has been widely studied under the two aspects of increasing the quality of the results and accelerating the computational processes. This chapter provides theoretic background on stereo vision systems and discusses architectures and implementations for real-time applications.
Christian Banz +2 more
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In-situ concrete slump test incorporating deep learning and stereo vision
Automation in Construction, 2021Seunghee Park, Sangyoon Chin
exaly
Automated concrete crack evaluation using stereo vision with two different focal lengths
Automation in Construction, 2022Sung-Han Sim +2 more
exaly