Real-time Rotation Invariant Hand Tracking Using 3D Data - Rosdiyana, Samad; M. Zabri, Abu Bakar; Pebrianti, Dwi; Nicolaas Lim, Yong Aan (2014)
Hand tracking is a common task in a gesture recognition system. Many techniques have been introduced to make successful hand tracking. In hand tracking system, most of previous works tracked the hand position using attached marker on hands. Several researchers used color image for skin color detection. However, using marker based need to attach marker on hands or wear glove to make hand can be detected. When use color information needs to extract many different skin color. Furthermore, the lighting and background in the situation also need to be concerned to avoid cluttered background that can affect the detection and tracking. This paper presents the real-time hand tracking using three dimensional (3D) data. This 3D data is coming from the Kinect sensor, which it can work in real-time. 3D data from Kinect sensor is depth image data and it can be used to detect and track the motion of hand. This paper proposes hand tracking method using hand tracker algorithm released by NiTE, hand’s segmentation method, hand contour detection and center of palm detection. The hand’s segmentation method consists of ROI of hand’s area and background subtraction. The propose hand tracking algorithm is rotation invariant, since it can detects and tracks various rotations of hand and it is also can remove unwanted object (noise) that also moving parallel with hand's position.