Stereo and Motion Based 3D High Density Object Tracking

Junli Tao, Benjamin Risse, Xiaoyi Jiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In order to understand the behavior of adult Drosophila melanogaster (fruit flies), vision-based 3D trajectory reconstruction methods are adopted. To improve the statistical strength of subsequent analysis, high-throughput measurements are necessary. However, ambiguities in both stereo matching and temporal tracking appear more frequently in high density situations, aggravating the complexity of the 3D tracking situation. In this paper we propose a high density object tracking algorithm. Instead of approximating trajectories for all frames in a direct manner, in ambiguous situations, tracking is terminated to generate robust tracklets based on the modified tracking-by-matching method. The terminated tracklets are linked to ongoing (unterminated) tracklets with minimum linking cost in an on-line fashion. Furthermore, we introduce a set of new evaluation metrics to analyze the tracking results. These metrics are used to analyse the effect of detection noise and compare our tracking algorithm with two state-of-the-art 3D tracking methods based on simulated data with hundreds of flies. The results indicate that our proposed algorithm outperforms both, the tracking-by-matching algorithm and a global correspondence selection approach.
Original languageEnglish
Title of host publicationImage and Video Technology
Subtitle of host publication6th Pacific-Rim Symposium, PSIVT 2013, Guanajuato, Mexico, October 28-November 1, 2013. Proceedings
PublisherSpringer
Pages136-148
Number of pages13
ISBN (Electronic)978-3-642-53842-1
ISBN (Print)978-3-642-53841-4
DOIs
Publication statusPublished - 2014

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin Heidelberg
Volume8333
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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