Hand Detection from Cluttered Images Based on a Hierarchical Strategy

Due to the variations of hand posture and the intricacy of environment/background, hand detection is a challenging task in human-computer and human-robot interactions. A hierarchical method is proposed in this paper to detect hand from images with cluttered background. In order to remove the most skin-like background of the image, upper body is detected from the image in the first hierarchy. Secondly, a novel approach, which combines samples threshold with experiential threshold, is proposed to detect skin/skin-like regions in images, and then skin regions are obtained according to the thresholds of area and length-width ratio of connected areas. At last, hand patches are determined by the hand model which is produced by support vector machine. The efficiency of this method is proved by corresponding experiments in hand detection in our dataset.

[1]  Zhan Song,et al.  Hand detection using multi-resolution HOG features , 2012, 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[2]  Stan Sclaroff,et al.  An alignment based similarity measure for hand detection in cluttered sign language video , 2009, 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[3]  Ying Wu,et al.  View-independent recognition of hand postures , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[4]  David G. Stork,et al.  Pattern Classification , 1973 .

[5]  Franc Solina,et al.  15 seconds of fame - an interactive, computer-vision based art installation , 2002, 7th International Conference on Control, Automation, Robotics and Vision, 2002. ICARCV 2002..

[6]  Chung-Lin Huang,et al.  Hand gesture recognition using a real-time tracking method and hidden Markov models , 2003, Image Vis. Comput..

[7]  Toshi Takamori,et al.  Multi-Modal Interaction of Human and Home Robot in the Context of Room Map Generation , 2002, Auton. Robots.

[8]  Franc Solina,et al.  An Automatic Human Face Detection Method , 1999 .

[9]  Sung Kwan Kang,et al.  Color Based Hand and Finger Detection Technology for User Interaction , 2008, 2008 International Conference on Convergence and Hybrid Information Technology.

[10]  Laurent Bonnaud,et al.  A Human Body Analysis System , 2006, EURASIP J. Adv. Signal Process..

[11]  Samir I. Shaheen,et al.  Sign language recognition using a combination of new vision based features , 2011, Pattern Recognit. Lett..

[12]  Toshi Takamori,et al.  Human detection and localization at indoor environment by home robot , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[13]  Martin Saerbeck,et al.  Recent methods and databases in vision-based hand gesture recognition: A review , 2015, Comput. Vis. Image Underst..

[14]  Mircea Nicolescu,et al.  Vision-based hand pose estimation: A review , 2007, Comput. Vis. Image Underst..

[15]  Wei-Che Chen,et al.  Region-Based and Content Adaptive Skin Detection in Color Images , 2007, Int. J. Pattern Recognit. Artif. Intell..

[16]  Alexander H. Waibel,et al.  Skin-Color Modeling and Adaptation , 1998, ACCV.

[17]  Euntai Kim,et al.  A part-based rotational invariant hand detection , 2013, 2013 International Conference on Fuzzy Theory and Its Applications (iFUZZY).

[18]  Haitham Sabah Badi,et al.  Hand posture and gesture recognition technology , 2014, Neural Computing and Applications.