Abstract
Object tracking remains one of the critical challenges in visual surveillance. It is difficult to track each moving object in a crowded scene. This paper proposed a new approach to track moving objects for longer duration. First, key points are tracked for short duration using state-of-the-art feature tracker. Next, the features are grouped and linked in spatiotemporal domain. Finally, we create a single trajectory for each object or a group of similar objects. We have tested the method on publicly available video datasets where more than 100 people were moving randomly. The results reveal that the proposed method can be highly effective to extract long-duration trajectories from the curtailed tracklets obtained using short-duration feature tracker.
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Ahmed, S.A., Dogra, D.P., Kar, S., Roy, P.P. (2018). Extraction of Long-Duration Moving Object Trajectories from Curtailed Tracks . In: Chaudhuri, B., Kankanhalli, M., Raman, B. (eds) Proceedings of 2nd International Conference on Computer Vision & Image Processing . Advances in Intelligent Systems and Computing, vol 704. Springer, Singapore. https://doi.org/10.1007/978-981-10-7898-9_26
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DOI: https://doi.org/10.1007/978-981-10-7898-9_26
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