@inproceedings{b6a4a769718d4fbf89e1ddb59268695d,
title = "Self-balance motion and appearance model for multi-object tracking in uav",
abstract = "Under the tracking-by-detection framework, multi-object tracking methods try to connect object detections with target trajectories by reasonable policy. Most methods represent objects by the appearance and motion. The inference of the association is mostly judged by a fusion of appearance similarity and motion consistency. However, the fusion ratio between appearance and motion are often determined by subjective setting. In this paper, we propose a novel self-balance method fusing appearance similarity and motion consistency. Extensive experimental results on public benchmarks demonstrate the effectiveness of the proposed method with comparisons to several state-of-the-art trackers.",
keywords = "Multi-object tracking, Neural networks, UAV",
author = "Hongyang Yu and Guorong Li and Weigang Zhang and Hongxun Yao and Qingming Huang",
note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 1st ACM International Conference on Multimedia in Asia, MMAsia 2019 ; Conference date: 15-12-2019 Through 18-12-2019",
year = "2019",
month = dec,
day = "15",
doi = "10.1145/3338533.3366561",
language = "英语",
series = "1st ACM International Conference on Multimedia in Asia, MMAsia 2019",
publisher = "Association for Computing Machinery, Inc",
booktitle = "1st ACM International Conference on Multimedia in Asia, MMAsia 2019",
}