Active Histogram of Oriented Gradient Based Learning for Free Palm Tracking

  • Shuai ZhangEmail author
  • Xiang Chen
  • Kongqiao Wang
  • Jiangwei Li
  • Yanwei Pang
  • He Yan
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 133)


Hand detection is a challenging research field in computer vision due tothe high freedom of hand for discrimination especially under low imaging conditions. In this paper, we mainly develop a novel feature that we called active Histogram of Oriented Gradient (aHOG) for palm detection inunconstrained grey-level images. Toovercome the limitationsof HOG, we apply local PCA, which is a feature synthesisprocedure, to original HOG feature sets. So that the output feature takesshorter description length and are less insensitive to light variations and background clusters, without much performance penalty. Then the features are combined with LBP for better palm information mining in linear SVM for classification. Besides, we use a scale partitionstrategy to achieve fast palm tracking. In our experiments, the performance is demonstrated to be very effective on the infrared palm database collected by ourselves, which involve rich inter-plane and out-of-plane rotations.


palmtracking active histogram of oriented gradient feature synthesis 


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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • Shuai Zhang
    • 1
    Email author
  • Xiang Chen
    • 1
  • Kongqiao Wang
    • 2
  • Jiangwei Li
    • 2
  • Yanwei Pang
    • 3
  • He Yan
    • 3
  1. 1.Department of Electrical Science and TechnologyUniversity of Science and Technology of ChinaHefeiChina
  2. 2.Nokia Research CenterBeijingChina
  3. 3.Department of Electrical and Information EngineeringTianjin UniversityTianjinChina

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