Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Multi-object Tracking in Video Sequences Based on Background Subtraction and SIFT Feature Matching
ICCIT '09 Proceedings of the 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology
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In this paper, we present an algorithm for tracking objects in road traffic sequences which is based on coherent strategy. This strategy relies on two times processing. Firstly, a Short-Term Processing (STP) based on spatial analysis and multilevel region descriptors matching allows identification of objects interactions and particular objects states. Secondly, a Long- Term Processing (LTP) is applied to cope with track management issues. In fact LTP feedbacks objects and their corresponding regions in each frame to update tracked object attributes. In case of merging objects, attributes are obtained using Template matching. An experimental study by quantitative and qualitative evaluations shows that the proposed approach can deal with multiple rigid objects whose sizes vary over time. The obtained results prove that our method can provide an effective and stable road objects tracks.