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线上线下结合的实时手势跟踪系统 被引量：2

Hand gesture tracking system based on online and offline
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摘要 手势识别跟踪一般采用线下训练分类器,不能有效检测跟踪形变的手势,针对手势形变及在窗口的暂时性消失等问题,提出了一种通过线下训练结合线上提取样本对分类器进行训练的检测方法,同时采用跟踪-检测-学习(TLD)的方法不断对跟踪器的结果进行纠正。试验结果表明,本算法对手势形变、短暂消失具有很好的适应性,与TLD算法相比较具有更好的稳定性。 Hand gesture recognition and tracking methods usually adopt offline training classifier,but the deformation of hand gesture can cause drift problem.In order to achieve more stability long time tracking,a novel detection method based on offline and online was presented,combined with TLD method to revise tracker.Experimental result shows this system could achieve more stability in hand gesture deformation and provisional disappear and it is more stable than TLD algorithm.
作者 王超 崔更申 黄廷辉 余益民
机构地区 桂林电子科技大学计算机科学与工程学院
出处 《桂林电子科技大学学报》 2012年第2期125-128,共4页 Journal of Guilin University of Electronic Technology
基金 广西自然科学基金(桂科青0728090)
关键词 手势识别 手势跟踪 Haar特征级联器 线上检测器 hand gesture recognition hand gesture tracking Haar cascade classifier online classifier
分类号 TP391.4 [自动化与计算机技术—计算机应用技术]
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参考文献9

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同被引文献12

  • 1Jalaleddin S,Rad M,Kaveh M,et al. Classification of rice varieties using optimal color and texture features and BP neural networks[C]//Machine Vision and Image Pro- cessing (MVIP), 2011.
  • 2Chaudry Q,Sharma Y, Raza S H,et al. Development of a novel 2D color map for interactive segmentation of his- tological images[C]// 9th IEEE International Symposi- um on Biomedical Imaging (ISBI) ,2012 :178-181.
  • 3Zhao Hongxia, Wang Tao. Study on conversion method of color space under a big color gamut[C]//2007 Inter- national Conference on Computational Intelligence and Security, 2007 : 386-390.
  • 4Li Z, Xue L, Tan F. Face detection in complex back- ground based on skin color features and improved Aria- Boost algorithms[C]//2010 IEEE international Confer- ence on Progress in Informatics and Computing, 2010: 723-727.
  • 5Lee S, Kwak Y,Kim Y J, et al. Contrast-preserved chro- ma enhancement technique using YCbCr color space[J]. IEEE Transactions on Consumer Electronics, 2012, 58 (2) :641-645.
  • 6Viola P,Jones M. Rapid object detection using a boosted cascade of simple features[C]//Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition,2001:511518.
  • 7Cheng Wenchang, Mao Jhanding. A cascade classifier using Adaboost algorithm and support vector machine for pedestrian detection[C]//Systems, Man, and Cy- bernetics (SMC) ,2011 : 1430-1435.
  • 8李文辉,倪洪印.一种改进的Adaboost训练算法[J].吉林大学学报（理学版）,2011,49(3):498-504. 被引量：23
  • 9文学志,方巍,郑钰辉.一种基于类Haar特征和改进AdaBoost分类器的车辆识别算法[J].电子学报,2011,39(5):1121-1126. 被引量：87
  • 10包涵,黄学航,陆星家.TLD目标追踪算法研究[J].宁波工程学院学报,2012,24(1):52-54. 被引量：4

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桂林电子科技大学学报
2012年 第2期

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