Binocular stereo matching method based on structure tensor

Xiaowei Song; Manyi Yang; Yubo Fan; Lei Yang

doi:10.1117/12.2246470

31 October 2016 Binocular stereo matching method based on structure tensor

Xiaowei Song, Manyi Yang, Yubo Fan, Lei Yang

Proceedings Volume 10020, Optoelectronic Imaging and Multimedia Technology IV; 100201B (2016) https://doi.org/10.1117/12.2246470
Event: SPIE/COS Photonics Asia, 2016, Beijing, China

Abstract

In a binocular visual system, to recover the three-dimensional information of the object, the most important step is to acquire matching points. Structure tensor is the vector representation of each point in its local neighborhood. Therefore, structure tensor performs well in region detection of local structure, and it is very suitable for detecting specific graphics such as pedestrians, cars and road signs in the image. In this paper, the structure tensor is combined with the luminance information to form the extended structure tensor. The directional derivatives of luminance in x and y directions are calculated, so that the local structure of the image is more prominent. Meanwhile, the Euclidean distance between the eigenvectors of key points is used as the similarity determination metric of key points in the two images. By matching, the coordinates of the matching points in the detected target are precisely acquired. In this paper, experiments were performed on the captured left and right images. After the binocular calibration, image matching was done to acquire the matching points, and then the target depth was calculated according to these matching points. By comparison, it is proved that the structure tensor can accurately acquire the matching points in binocular stereo matching.

Citation Download Citation

Xiaowei Song, Manyi Yang, Yubo Fan, and Lei Yang "Binocular stereo matching method based on structure tensor", Proc. SPIE 10020, Optoelectronic Imaging and Multimedia Technology IV, 100201B (31 October 2016); https://doi.org/10.1117/12.2246470

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KEYWORDS

Cameras

Calibration

Principal component analysis

3D modeling

Error analysis

Target detection

Visualization

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