@inproceedings{011e92d4904f4072a500fd5d9a28a9c8,
title = "Automatic object tracking in aerial videos via spatial-temporal feature clustering",
abstract = "Automatic detecting and tracking the objects from UAV videos is very important and challenging for both tactical and security applications. We present a robust object tracking system that is able to track multiple objects robustly in UAV videos. The main characteristics of the proposed system include: (1)A novel feature clustering based multiple objects tracking framework is proposed, which performs much better than the traditional foreground-blob- tracking-based methods. (2)Optical flow features are clustered both in spatial and temporal dimension to track multiple objects robustly even in the case of multiple objects cross moving. Extensive experimental results with quantitative and qualitative analysis demonstrate the robustness and effectiveness of our algorithm.",
keywords = "Multiple objects tracking, optical flow, spatial-temporal trajectory clustering",
author = "Xiaomin Tong and Yanning Zhang and Tao Yang and Wenguang Ma",
year = "2013",
doi = "10.1007/978-3-642-42057-3_11",
language = "英语",
isbn = "9783642420566",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "78--85",
booktitle = "Intelligence Science and Big Data Engineering - 4th International Conference, IScIDE 2013, Revised Selected Papers",
note = "4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013 ; Conference date: 31-07-2013 Through 02-08-2013",
}