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. © Springer-Verlag 2004.
CITATION STYLE
Kang, H. B., & Cho, S. H. (2004). Short-term memory-based object tracking. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3212, 597–605. https://doi.org/10.1007/978-3-540-30126-4_73
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