Hand gesture recognition using infrared imagery provided by leap motion controller

Hand gestures are one of the main alternatives for Human- Computer Interaction. For this reason, a hand gesture recognition system using near-infrared imagery acquired by a Leap Motion sensor is proposed. The recognition system directly characterizes the hand gesture by computing a global image descriptor, called Depth Spatiograms of Quantized Patterns, without any hand segmentation stage. To deal with the high dimensionality of the image descriptor, a Compressive Sensing framework is applied, obtaining a manageable image feature vector that almost preserves the original information. Finally, the resulting reduced image descriptors are analyzed by a set of Support Vectors Machines to identify the performed gesture independently of the precise hand location in the image. Promising results have been achieved using a new hand-based near-infrared database