Abstract
In this paper, we propose a new tracking method that adapts itself to suddenly changing appearance. The proposed method is based on color-based particle filtering. A short-term memory model is introduced to handle the cases of sudden appearance changes, occlusion, disappearance and reappearance of tracked objects. A new target model update method is implemented. Our method is robust and versatile for a modest computational cost. Desirable tracking results are obtained.
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Kang, HB., Cho, SH. (2004). Short-Term Memory-Based Object Tracking. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30126-4_73
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DOI: https://doi.org/10.1007/978-3-540-30126-4_73
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23240-7
Online ISBN: 978-3-540-30126-4
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