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Highly non-rigid video object tracking using segment-based object candidates
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DOI：10.1007/s11042-016-3563-3.png)
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摘要
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A novel scheme for non-rigid video object tracking using segment-based object candidates is proposed in this paper. Rather than using a conventional bounding box, the tracker is based on segments and considers the target object to be a combination of segments, where the hierarchical hue-saturation-value histogram is extracted as a feature. The objectness method is employed and integrated into the tracker to generate candidates for a similarity measure. Moreover, segment-based motion weights are introduced to give higher weights to candidates with motion consistency. A confidence-collecting scheme is proposed for similar candidates. To validate our method, experiments were conducted using several image sequences with different non-rigid challenges. The experimental results show that the proposed scheme can achieve better performance than other state-of-the-art methods.
Keyword:
Highly non-rigid object
Tracking
Segment-based
Objectness
Motion weights
Appearance model
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期刊
IF:
3
论文数:
2.0W
被引数:
3.2W
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