ECCV 2016: The 14th European Conference on Computer Vision.

CDT: Cooperative Detection and Tracking
for Tracing Multiple Objects in Video Sequences

Han-Ul Kim
hanulkim@mcl.korea.ac.kr
Korea University

Chang-Su Kim
changsukim@korea.ac.kr
Korea University

Abstract

A cooperative detection and model-free tracking algorithm, referred to as CDT, for multiple object tracking is proposed in this work. The proposed CDT algorithm has three components: object detector, forward tracker, and backward tracker. First, the object detector detects targets with high confidence levels only to reduce spurious detection and achieve a high precision rate. Then, each detected target is traced by the forward tracker and then by the backward tracker to restore undetected states. In the tracking processes, the object detector cooperates with the trackers to handle appearing or disappearing targets and to refine inaccurate state estimates. With this detection guidance, the model-free tracking can trace multiple objects reliably and accurately. Experimental results show that the proposed CDT algorithm provides excellent performance on a recent benchmark. Furthermore, an online version of the proposed algorithm also excels in the benchmark.

Demo

We evaluate the performance of the proposed tracker on the MOT challenge 2015 dataset.

Publication

Han-Ul Kim and Chang-Su Kim, "CDT: Cooperative Detection and Tracking for Tracing Multiple Objects in Video Sequences," in Proc ECCV, Oct. 2016. [pdf] [source code]