题目/Title：Hand Gesture Recognition with Multi-Scale Weighted Histogram of Contour Direction (MSWHCD) Normalization for Wearable Applications

作者/Author：任仡奕,谢翔,李国林,王志华
                        Yiyi Ren,Xiang Xie,Guolin Li,Zhihua Wang

期刊/Journal：IEEE Transactions on Circuits and Systems for Video Technology

年份/Issue Date：2016Sept.

卷（期）及页码/Volume（No.）&pages：Vol.pp, No.99, pp. 1 - 1

摘要/Abstract：
This paper proposes a static hand gesture recognition method with low computation and memory consumptions for wearable applications. The hand contour is chosen as the hand gesture feature and SVM is used to classify the feature. A Multi-Scale Weighted Histogram of Contour Direction (MSWHCD) based direction normalization is proposed to ensure a good recognition performance. In order to improve efficiency, the proposed histogram only counts the direction of contour point to focus on the most significant hand feature in the first person view of wearable devices. Based on hand anatomy, the proposed histogram is weighted by considering each contour point’s position and direction jointly using Direction-Angle Map (DAM), so as to ensure the robustness. Experimental results show that the proposed method can give a recognition accuracy of 97.1% with a frame rate of 30fps on PC.