Saliency Detection Based Region Extraction for Pedestrian Detection System with Thermal Imageries
Author:
Affiliation:
1. College of Information Science and Engineering, Northeastern University
2. Faculty of Robot Science and Engineering, Northeastern University
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Subject
Applied Mathematics,Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Signal Processing
Link
https://www.jstage.jst.go.jp/article/transfun/E101.A/1/E101.A_306/_pdf
Reference19 articles.
1. [1] Y. Ma, X. Wu, G. Yu, Y. Xu, and Y. Wang, “Pedestrian detection and tracking from low-resolution unmanned aerial vehicle thermal imagery,” Sensors, vol.16, no.4, p.446, 2016. 10.3390/s16040446
2. [2] J.H. Lee, J.S. Choi, E.S. Jeon, Y.G. Kim, L. Toan Thanh, K.Y. Shin, H.C. Lee, and K.R. Park, “Robust pedestrian detection by combining visible and thermal infrared cameras,” Sensors, vol.15, no.5, pp.10580-10615, 2015. 10.3390/s150510580
3. [3] N.L. Zhang, B. Wu, and R. Nevatia, “Pedestrian detection in infrared images based on local shape features,” 2007 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2007. 10.1109/cvpr.2007.383452
4. [4] S.K. Biswas and P. Milanfar, “Linear support tensor machine with lsk channels: Pedestrian detection in thermal infrared images,” IEEE Trans. Image Process., vol.26, no.9, pp.4229-4242, Sept. 2017. 10.1109/tip.2017.2705426
5. [5] J. Li, W. Gong, W. Li, and X. Liu, “Robust pedestrian detection in thermal infrared imagery using the wavelet transform,” Infrared Phys. Techn., vol.53, no.4, pp.267-273, 2010. 10.1016/j.infrared.2010.03.005
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