Thermal-depth matching in dynamic scene based on affine projection and feature registration

Hongyu Wang; Tong Jia; Chengdong Wu; Yongqiang Li

doi:10.1117/12.2312390

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5 March 2018 Thermal-depth matching in dynamic scene based on affine projection and feature registration

Hongyu Wang, Tong Jia, Chengdong Wu, Yongqiang Li

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Proceedings Volume 10710, Young Scientists Forum 2017; 107100P (2018) https://doi.org/10.1117/12.2312390
Event: Young Scientists Forum 2017, 2017, Shanghai, China

Abstract

This paper aims to study the construction of 3D temperature distribution reconstruction system based on depth and thermal infrared information. Initially, a traditional calibration method cannot be directly used, because the depth and thermal infrared camera is not sensitive to the color calibration board. Therefore, this paper aims to design a depth and thermal infrared camera calibration board to complete the calibration of the depth and thermal infrared camera. Meanwhile a local feature descriptors in thermal and depth images is proposed. The belief propagation matching algorithm is also investigated based on the space affine transformation matching and local feature matching. The 3D temperature distribution model is built based on the matching of 3D point cloud and 2D thermal infrared information. Experimental results show that the method can accurately construct the 3D temperature distribution model, and has strong robustness.

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Hongyu Wang, Tong Jia, Chengdong Wu, and Yongqiang Li "Thermal-depth matching in dynamic scene based on affine projection and feature registration", Proc. SPIE 10710, Young Scientists Forum 2017, 107100P (5 March 2018); https://doi.org/10.1117/12.2312390

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