by Tao, J, Franke, U and Klette, R
Abstract:
Occlusion has long been a core challenge for multi-target tracking tasks. In this paper we present context-based tracking strategies and demonstrate those for two very different types of targets, namely vehicles and fruit flies, representing examples of different target categories (e.g. individually identifiable with relatively consistent trajectories versus nearly identical targets with highly irregular trajectories). Those two classes of targets are also recorded with either mobile or static camera systems, and they represent either long-term or high-frequency occlusion scenarios, respectively. Occlusions among rigid vehicles have various occlusion patterns because of the mobile recording platform and the dynamic traffic environment. In contrast, a high-density scene of fruit flies contains hundreds of targets where occlusion is relatively short, but the frequency of occlusions is very high. In this paper we propose tracking systems based on context information, and show that those are able to address both application scenarios of target tracking. The proposed strategy outperforms state-of-the-art methods in both cases. Experimental results also demonstrate the efficiency of the proposed systems for occlusion handling.
Reference:
Context-based multi-target tracking with occlusion handling (Tao, J, Franke, U and Klette, R), In Machine Vision and Applications, Springer Verlag, 2016.
Bibtex Entry:
@article{tao2016context-basedhandling,
author = "Tao, J and Franke, U and Klette, R",
journal = "Machine Vision and Applications",
month = "May",
pages = "1--11",
publisher = "Springer Verlag",
title = "Context-based multi-target tracking with occlusion handling",
year = "2016",
abstract = "Occlusion has long been a core challenge for multi-target tracking tasks. In this paper we present context-based tracking strategies and demonstrate those for two very different types of targets, namely vehicles and fruit flies, representing examples of different target categories (e.g. individually identifiable with relatively consistent trajectories versus nearly identical targets with highly irregular trajectories). Those two classes of targets are also recorded with either mobile or static camera systems, and they represent either long-term or high-frequency occlusion scenarios, respectively. Occlusions among rigid vehicles have various occlusion patterns because of the mobile recording platform and the dynamic traffic environment. In contrast, a high-density scene of fruit flies contains hundreds of targets where occlusion is relatively short, but the frequency of occlusions is very high. In this paper we propose tracking systems based on context information, and show that those are able to address both application scenarios of target tracking. The proposed strategy outperforms state-of-the-art methods in both cases. Experimental results also demonstrate the efficiency of the proposed systems for occlusion handling.",
doi = "10.1007/s00138-016-0770-x",
issn = "0932-8092",
eissn = "1432-1769",
keyword = "Context",
keyword = "Occlusion",
keyword = "Stereo vision",
keyword = "Tracking",
language = "eng",
day = "25",
publicationstatus = "accepted",
}