Robust visual tracking via spatio-temporal cue integration

Yang He; Mingtao Pei; Min Yang; Yuwei Wu; Wei Liang

doi:10.1117/12.2050313

10 January 2014 Robust visual tracking via spatio-temporal cue integration

Yang He, Mingtao Pei, Min Yang, Yuwei Wu, Wei Liang

Proceedings Volume 9069, Fifth International Conference on Graphic and Image Processing (ICGIP 2013); 90690Z (2014) https://doi.org/10.1117/12.2050313
Event: Fifth International Conference on Graphic and Image Processing, 2013, Hong Kong, China

Abstract

Appearance modeling is an important and yet challenging issue for online visual tracking due to the accumulation of errors which is prone to potential drifting during the self-updating with newly obtained results. In this paper, we propose a novel online tracking algorithm using spatio-temporal cue integration. Specifically, the object is represented as a set of local patches with respect to the spatial cue. In terms of the temporal cue, we keep the appearance models at different time and do appearance updating alternately. Taking full advantage of both historical and current information of the tracked object, the drift problem is alleviated. We also develop an effective cue quality measurement that combines similarity and motion information. Both qualitative and quantitative evaluations on challenging video sequences demonstrate that the proposed algorithm performs comparable against the state-of-the-art methods.

Citation Download Citation

Yang He, Mingtao Pei, Min Yang, Yuwei Wu, and Wei Liang "Robust visual tracking via spatio-temporal cue integration", Proc. SPIE 9069, Fifth International Conference on Graphic and Image Processing (ICGIP 2013), 90690Z (10 January 2014); https://doi.org/10.1117/12.2050313

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KEYWORDS

Motion models

Optical tracking

Detection and tracking algorithms

Video

Large Synoptic Survey Telescope

Quality measurement

Performance modeling

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