A survey of multi-object video tracking algorithms

Abstract

Video multi-object tracking is one of the important research topics in the field of computer vision, which is widely used in military and civil areas. At present, the research of single object tracking algorithm is quite mature, however the research of multi-object tracking is still ongoing. This paper focuses on four important stages in the multi-object tracking process: feature extraction, detector, data association and the tracker. The feature extraction part introduces the current methods of feature extraction, as well as the merits and demerits of each method; In the stage of detection, the tracking effect of the object appearance model in specific applications is described, and then the paper analyze the multi-object tracking algorithm based on detection and tracking as well as the multi-object tracking algorithm based on deep learning; In the tracking stage, the establishment of object motion model and multi-object tracking with different tracker hybrid algorithm are introduced; During the stage of data association, the paper introduce the multi-object tracking based on energy minimization and commonly used data association algorithm, respectively. Then the current mainstream datasets and evaluation methods are introduced. Finally, the future development of the multi-object tracking is discussed and forecasted.