Hand Gesture Recognition Using Kinect's Geometric and HOG Features
Marouane Hamda, Abdelhak Mahmoudi · 2017
Hand gesture recognition plays an important role in human computer interaction (HCI). Despite the recent progress, the accuracy of up-to-date methods is still not satisfactory. In this work, we proposed a comparative study to recognize six hand gestures in real time using the Kinect sensor. First, we developed a tracking method of the hand in the scene where the center of the palm is detected using depth data and projected into the color image. Second, geometric features were extracted from depth image and Histogram of Oriented Gradients (HOG) descriptors from the color image. Finally, based on those extracted features, a support vector machines (SVM) and an artificial neural network (ANN) are trained and compared.