An improved hu-moment algorithm in gesture recognition based on kinect sensor

被引：4
作者：
机构：
[1] Department of Information Engineering, Guangdong Polytechnic, Foshan 528041, Guangdong
[2] Synthesis Department, Guangdong Power Gird Corporation Foshan Power Supply Bureau, Foshan, Guangdong
来源：
Li, G. | 1600年 / Asian Network for Scientific Information卷 / 12期
关键词：
Depth image; Gesture recognition; Hu-moment; Scale factor;
D O I：
10.3923/itj.2013.2963.2968
中图分类号：
学科分类号：
摘要：
In order to solve the problem of variability of gesture recognition, The Kinect sensor and the improved Hu-moment is used in this study. Depth image, after image restoration, its feature data is extracted using depth threshold is obtained based on Kinect. Then the scale factor is added to the Hu-moment, so that the invariant moments contain more detail characteristics of gesture and have relationship with geometry but not scaling. For illustration, a dress fitting system example is utilized to interpret the algorithm. Empirical results show that the gesture recognition method is performed correctly in illumination and complex background. So the method of gesture recognition has invariance in image rotation, scaling and translation and has robustness to background interference. © 2013 Asian Network for Scientific Information.
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收藏
页码：2963 / 2968
页数：5
相关论文
共 12 条
  • [1] Chen R.S., The scale invariability analysis of Hu moments for digital image recognition (in Chinese), Microcomput. ITS Appli., 30, pp. 29-31, (2011)
  • [2] Hu M.K., Visual pattern recognition by moment invariants, IRE Trans. Inform. Theo., 8, pp. 179-187, (1962)
  • [3] Hua B., Xia L.N., Sign language recognition based on Hu invariant moments and euclidean distance (InChinese), Comput. Eng. Des., 32, pp. 615-618, (2011)
  • [4] Ikemura S., Fujiyoshi H., Real-time human detection using relational depth similarity features, Computer Vision-ACCV 2010, 10th Asian Conference on Computer Vision, 6495, pp. 25-38, (2011)
  • [5] Kang Y.S., Ho Y.S., Disparity map generation for color image using TOF depth camera, Proceedings of the 3DTV-Conference: The True Vision-Capture, Transmission and Display of 3D Video, pp. 1-4, (2011)
  • [6] Li G.S., Luo J.H., Zhang J., Design and realization of somatosensory dress fitting system based on kinect (In Chinese), Tsinghua Sei. Technol., 3, pp. 48-50, (2012)
  • [7] Li H., Ding L., Ran G., Analysis of human identification based on kinect depth image, Digital Commun., 4, pp. 21-26, (2012)
  • [8] Li Y., Hand gesture recognition using kinect, Proceedings of 3rd International Conference on Software Engineering and Service Science, pp. 196-199, (2012)
  • [9] Liu J., Liu Y., Yan C., Feature extraction technique based on the perceptive invariability, Proceedings of the 5th International Conference on Fuzzy Systems and Knowledge Discovery, pp. 551-554, (2008)
  • [10] Smisek J., Jancosek M., Pajdla T., 3D with kinect, Proceedings of the IEEE International Conference on Computer Vision Workshops, pp. 1154-1160, (2011)
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