Untargeted attack on targeted-label for multi-label image classification

Yangfei Lin; Peng Qiao; Yong Dou

doi:10.1117/12.2589445

27 January 2021 Untargeted attack on targeted-label for multi-label image classification

Yangfei Lin, Peng Qiao, Yong Dou

Proceedings Volume 11720, Twelfth International Conference on Graphics and Image Processing (ICGIP 2020); 117201P (2021) https://doi.org/10.1117/12.2589445
Event: Twelfth International Conference on Graphics and Image Processing, 2020, Xi'an, China

Abstract

The current 3D point cloud feature extraction algorithms are mostly based on geometric features of points. And the distribution of feature points is so messy to accurately locate. This paper proposes a point cloud feature extraction algorithm using 2D-3D transformation. By selecting three pairs of 2D image and 3D point cloud feature points, the conversion matrix of image and point cloud coordinates is calculated to establish a mapping relationship and then we realize the extraction of point cloud features. Experimental results show that compared with other algorithms, the algorithm proposed in this paper can extract the detailed features of point cloud more accurately.

Citation Download Citation

Yangfei Lin, Peng Qiao, and Yong Dou "Untargeted attack on targeted-label for multi-label image classification", Proc. SPIE 11720, Twelfth International Conference on Graphics and Image Processing (ICGIP 2020), 117201P (27 January 2021); https://doi.org/10.1117/12.2589445

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