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Quad binary pattern and its application in mean-shift tracking
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DOI：10.1016/j.neucom.2015.11.130.png)
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摘要
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This paper proposes a new local texture descriptor, called quad binary pattern (QBP). Compared with local binary pattern (LBP), the QBP is with stronger robustness for feature extraction under complex scene (e.g., luminance change, similar target and background color) and with lower computational complexity. To demonstrate its effectiveness, the proposed QBP is further applied on the mean-shift tracking, in which a joint color-QBP model is developed to effectively represent the color and texture characteristics of the target region. Extensive simulation results have demonstrated that the proposed algorithm is able to improve the tracking speed and accuracy, compared with the standard mean-shift tracking and joint color-LBP model based mean-shift tracking. (C) 2016 Elsevier B.V. All rights reserved.
Keyword:
Target tracking
Quad binary pattern
Mean-shift tracking
Joint color-QBP model
Feature extraction
期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
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引用论文
PLBP: An effective local binary patterns texture descriptor with pyramid representation.png)
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