@inproceedings{84000812ebd242739371f8ac71b89152,
title = "Online multi-person tracking based on metric learning",
abstract = "The correct associations of detections and tracklets are the key to online multi-person tracking. Good appearance models can guide data association and play an important role in the association. In this paper, we construct a discriminative appearance model by using metric learning which can obtain accurate appearance affinities with human appearance variations. The novel appearance model can significantly guide data association. Furthermore, the model is learned incrementally according to the association results and its parameters are automatically updated to be suitable for the next online tracking. Based on an online tracking-by-detection framework, our method achieves reliable tracking of multiple persons even in complex scenes. Our experimental evaluation on publicly available data sets shows that the proposed online multiperson tracking method works well.",
keywords = "Appearance model, Metric learning, Multi-person tracking, Online tracking",
author = "Changyong Yu and Min Yang and Yanmei Dong and Mingtao Pei and Yunde Jia",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 17th Pacific-Rim Conference on Multimedia, PCM 2016 ; Conference date: 15-09-2016 Through 16-09-2016",
year = "2016",
doi = "10.1007/978-3-319-48890-5_13",
language = "English",
isbn = "9783319488899",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "130--140",
editor = "Enqing Chen and Yun Tie and Yihong Gong",
booktitle = "Advances in Multimedia Information Processing – 17th Pacific-Rim Conference on Multimedia, PCM 2016, Proceedings",
address = "Germany",
}