POI: Multiple Object Tracking with High Performance Detection and Appearance Feature
Abstract
Detection and learning based appearance feature play the central role in data association based multiple object tracking (MOT), but most recent MOT works usually ignore them and only focus on the hand-crafted feature and association algorithms. In this paper, we explore the high-performance detection and deep learning based appearance feature, and show that they lead to significantly better MOT results in both online and offline setting. We make our detection and appearance feature publicly available (https://drive.google.com/open?id=0B5ACiy41McAHMjczS2p0dFg3emM). In the following part, we first summarize the detection and appearance feature, and then introduce our tracker named Person of Interest (POI), which has both online and offline version (We use POI to denote our online tracker and KDNT to denote our offline tracker in submission.).
Cite
Text
Yu et al. "POI: Multiple Object Tracking with High Performance Detection and Appearance Feature." European Conference on Computer Vision Workshops, 2016. doi:10.1007/978-3-319-48881-3_3Markdown
[Yu et al. "POI: Multiple Object Tracking with High Performance Detection and Appearance Feature." European Conference on Computer Vision Workshops, 2016.](https://mlanthology.org/eccvw/2016/yu2016eccvw-poi/) doi:10.1007/978-3-319-48881-3_3BibTeX
@inproceedings{yu2016eccvw-poi,
title = {{POI: Multiple Object Tracking with High Performance Detection and Appearance Feature}},
author = {Yu, Fengwei and Li, Wenbo and Li, Quanquan and Liu, Yu and Shi, Xiaohua and Yan, Junjie},
booktitle = {European Conference on Computer Vision Workshops},
year = {2016},
pages = {36-42},
doi = {10.1007/978-3-319-48881-3_3},
url = {https://mlanthology.org/eccvw/2016/yu2016eccvw-poi/}
}