Real-Time Hand Gesture Recognition Based on the Depth Map for Human Robot Interaction - Minoo Hamissi; Karim Faez (Institute of Advanced Engineering and Science, 2013)
In this paper, we propose and implement a novel and real-time method for recognizing hand gestures using depth map. The depth map contains information relating to the distance of objects from a viewpoint. Microsoft’s Kinect sensor is used as input device to capture both the color image and its corresponding depth map. We first detect bare hand in cluttered background using distinct gray-level of the hand which is located near to the sensor. Then, scale invariance feature transform (SIFT) algorithm is used to extract feature vectors. Lastly, vocabulary tree along with K-means clustering method are used to partition the hand postures to ten simple sets as: