Weighted Pattern Vector for Object Tracking with the Use of Thermal Images
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-319-64674-9_5
Reference27 articles.
1. Kang, B.-D., Jeon, K.-H., Kyoung, D., Kim, S.-H., Hwang, J.-H. (2012). Multiple human body tracking based on normalized cross-correlation of average histogram using the fusion of color and thermal image sensor. In RO-MAN 2012. IEEE. doi: 10.1109/ROMAN.2012.6343785 .
2. Padole, C. N. ; Alexandre, L. A. (2010) Wigner distribution based motion tracking of human beings using thermal imaging. In 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). doi: 10.1109/CVPRW.2010.5543226 .
3. Ciric, I., Cojbasic, Z., Nikolic, V., Antic, D. (2013). Computationally intelligent system for thermal vision people detection and tracking in robotic applications. In 2013 11th International Conference on Telecommunication in Modern Satellite, Cable and Broadcasting Services (TELSIKS) (Vol. 02). doi: 10.1109/TELSKS.2013.6704447 .
4. Stolkin, R., Rees, D., Talha, M., & Florescu, I. (2012). Bayesian fusion of thermal and visible spectra camera data for mean shift tracking with rapid background adaptation. In Sensors. IEEE. doi: 10.1109/ICSENS.2012.6411350 .
5. Treptow, A., Cielniak, G., & Duckett, T. (2005) Active people recognition using thermal and grey images on a mobile security robot. In 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems. (IROS 2005). doi: 10.1109/IROS.2005.1545530 .
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