Integrating Color and Shape-Texture Features for Adaptive Real-Time Object Tracking
Integrating Color and Shape-Texture Features for Adaptive Real-Time Object Tracking
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DOI：
10.1109/tip.2007.914150
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发表时间：
2008-02
影响因子：
10.6
通讯作者：
Junqiu Wang;Y. Yagi
中科院分区：
文献类型：
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作者：
Junqiu Wang;Y. Yagi
我们将标准的Mean-Shift跟踪算法扩展到自适应跟踪器，根据其描述能力从颜色和形状-纹理线索中选择可靠的特征。目标模型根据初始模型和当前模型之间的相似度进行更新，使跟踪器具有更强的鲁棒性。使用具有挑战性的图像序列将该算法与其他跟踪器进行了比较，该算法具有更好的性能。
We extend the standard mean-shift tracking algorithm to an adaptive tracker by selecting reliable features from color and shape-texture cues according to their descriptive ability. The target model is updated according to the similarity between the initial and current models, and this makes the tracker more robust. The proposed algorithm has been compared with other trackers using challenging image sequences, and it provides better performance.