关键词: 动态手势, 局部敏感, 梯度方向直方图, 时空特征

Abstract: In order to improve the performance of dynamic hand gesture recognition in complex real scenes for human-computer interaction, a novel method named Temporal Locality Sensitive Histograms of Oriented Gradients（TLSHOG） is proposed to represent sequential variations and changeable spatial postures of human hands. And it certainly achieves effective dynamic hand gesture recognition in real time. Firstly, a training set for machine learning is established by recording several videos of human hands using normal PC cameras. After that, a single-frame feature is proposed to describe the spatial feature of hands, and a Temporal Pyramid（TP） method is further applied to describe the trajectories of dynamic hand gestures. At last, a multidimensional Support Vector Machine（SVM） classifier is build, and all dynamic hand gestures in testing set are then correctly recognized. The experimental results indicate that this new method is highly discriminative of dynamic hand gestures and robust to effects of complex backgrounds and illuminations.

Key words: dynamic hand gesture, locality sensitive, histogram of oriented gradients, spatial-temporal features