An Online LC-KSVD Based Dictionary Learning for Multi-target Tracking
In this paper, we propose a novel framework for multi-objects tracking on solving two kind of challenges. One is how to discriminate different targets with similar appearance, the other is distinct the single target with serious variation over time. The proposed framework extracts discriminative appearance information of different objects from historical recordings of all tracked targets by a label consistent K-SVD (LC-KSVD) dictionary learning method. We validated our proposed framework on three publicly available video sequences with some state-of-the-art approaches. The experiment results showed that our proposed method achieves competitive results with 7.7% improvement in MOTP.