A fast target depth perception method based on stereo structured light

Zhixin Long; Yuxuan Wang; Taoxin Tang; Jianguo Wu; Zemiao Yu; Hongyu Wang; Dongxue Li

doi:10.1117/12.2666830

4 April 2023 A fast target depth perception method based on stereo structured light

Zhixin Long, Yuxuan Wang, Taoxin Tang, Jianguo Wu, Zemiao Yu, Hongyu Wang, Dongxue Li

Proceedings Volume 12617, Ninth Symposium on Novel Photoelectronic Detection Technology and Applications; 126177C (2023) https://doi.org/10.1117/12.2666830
Event: 9th Symposium on Novel Photoelectronic Detection Technology and Applications (NDTA 2022), 2022, Hefei, China

Abstract

Structured light stereo vision depth perception is a key method in the fields of 3D contour reconstruction and human-computer interaction. To address the problem that the array-encoded raw image cannot be accurately localized due to artifacts when the target under test is moving rapidly, we propose a linear sparse depth perception method based on artifact analysis. Also, in order to effectively perceive the artefact parameters in motion, we design a heterogeneous coding model with grid line mode and array coding mode. To obtain the artifact width parameters of fast-moving objects under binocular vision, the artifact parameters were obtained based on a gradient ridge extraction method. Finally, to obtain the artefact analysis function required for depth perception of fast-moving targets, we used discrete artefact parameters to obtain a global artefact analysis function. Linear sparse depth information is obtained from the artifact parameter information in the binocular images, thus improving the speed and robustness of depth perception. Keywords: structured light; stereo vision; image segmentation; artifact analysis.

Citation Download Citation

Zhixin Long, Yuxuan Wang, Taoxin Tang, Jianguo Wu, Zemiao Yu, Hongyu Wang, and Dongxue Li "A fast target depth perception method based on stereo structured light", Proc. SPIE 12617, Ninth Symposium on Novel Photoelectronic Detection Technology and Applications, 126177C (4 April 2023); https://doi.org/10.1117/12.2666830

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