Abstract
Nowadays, pedestrian recognition in far-infrared images toward realizing a night vision system becomes a hot topic. However, sufficient performance could not be achieved by conventional schemes for pedestrian recognition in far-infrared images. Since the properties of far-infrared images are different from visible images, it is not known what kind of scheme is suitable for pedestrian recognition in far-infrared images. In this paper, a novel pedestrian recognition scheme combining boosting-based detection and skeleton-based stochastic tracking suitable for recognition in far-infrared images is proposed. Experimental results by using far-infrared sequences show the proposed scheme achieves highly accurate pedestrian recognition by combining accurate detection with few false positives and accurate tracking.
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Miyamoto, R. et al. (2006). Pedestrian Recognition in Far-Infrared Images by Combining Boosting-Based Detection and Skeleton-Based Stochastic Tracking. In: Chang, LW., Lie, WN. (eds) Advances in Image and Video Technology. PSIVT 2006. Lecture Notes in Computer Science, vol 4319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11949534_48
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DOI: https://doi.org/10.1007/11949534_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68297-4
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