3D object detection based on multi-view feature point matching

Tian Yang; Xinzhu Sang; Duo Chen; Nan Guo; Peng Wang; Xunbo Yu; Binbin Yan; Kuiru Wang; Chongxiu Yu

doi:10.1117/12.2548012

18 December 2019 3D object detection based on multi-view feature point matching

Tian Yang, Xinzhu Sang, Duo Chen, Nan Guo, Peng Wang, Xunbo Yu, Binbin Yan, Kuiru Wang, Chongxiu Yu

Proceedings Volume 11342, AOPC 2019: AI in Optics and Photonics; 113420O (2019) https://doi.org/10.1117/12.2548012
Event: Applied Optics and Photonics China (AOPC2019), 2019, Beijing, China

Abstract

The result of object detection based on deep learning may have errors or omissions due to the occlusion and background in object detection, which is an intractable problem. An effective method of improving object detection performance using multiple viewpoint images are proposed. By performing feature point matching on objects in the overlap between different views, groups of points with semantic information can be obtained. These point groups can be used to generate new detection boxes, which can correct error ones in the raw results. Experiments show that the proposed method is a viable solution, the recall is significantly improved.

Citation Download Citation

Tian Yang, Xinzhu Sang, Duo Chen, Nan Guo, Peng Wang, Xunbo Yu, Binbin Yan, Kuiru Wang, and Chongxiu Yu "3D object detection based on multi-view feature point matching", Proc. SPIE 11342, AOPC 2019: AI in Optics and Photonics, 113420O (18 December 2019); https://doi.org/10.1117/12.2548012

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