A novel hand gesture recognition method using Principal Directional Features

This paper presents a novel hand gesture recognition method based on Principal Directional Features (PDF). The image sequence is captured using a fixed mounted monocular camera to recognize dynamic gestures. Haar-like feature based cascaded classifier is used for hand area segmentation. Text based Principal Directional Features are extracted from the segmented images. Longest Common Subsequence algorithm is used to recognize the gestures from text based PDF. The Directional Gesture dataset is prepared containing complex dynamic gestures to test this system and achieved 94% accuracy in recognizing dynamic hand gestures.