A system for person-independent classification of hand postures against complex backgrounds in video images is presented. The system employs elastic graph matching, which has already been successfully applied for object and face recognition. We use the bunch graph technique to model variance in hand posture appearance between different subjects and variance in backgrounds. Our system does not n...

The intent of the paper is to apply computer vision technique to control the music player by CAMSHIFT algorithm. Based on the human hand activity, gesture and posture recognition are used to communicate with computers. Gesture is the physical movement of a hand, expressive of an idea. Posture is the static morph of a hand. In this paper skin colour segmentation is used for hand detection, after...

In this paper, we describe techniques for barehanded interaction between human and computer. Barehanded means that no device and no wires are attached to the user, who controls the computer directly with the movements of his/her hand. Our approach is centered on the needs of the user. We therefore define requirements for real-time barehanded interaction, derived from application scenarios and u...

We present a model-based method for hand posture recognition in monocular image sequences that measures joint angles, viewing angle, and position in space. Visual markers in form of a colored cotton glove are used to extract descriptive and stable 2D features. Searching a synthetically generated database of 2.6 million entries, each consisting of 3D hand posture parameters and the corresponding...

An approach making use of SURF feature and Adaboost for hand posture recognition is proposed. First the SURF key points are extracted to describe the blob or ridge-like structures from grey level images. These are potential points of interest that can be used to match with other images with similar structures. Then the statistic parameters of the tendency of gradient changes within small patche...

Integration of different modalities aims to increase the robustness of system and improves its performance in an unconstrained environment. With this motivation, the proposed research is focused on integrating two modalities such as hand gesture and posture in a unified framework where the criterion is measured by employing Particle Filter system. The proposed framework has two main modules: 1)...

This paper presents a new scheme for hand posture selection and recognition based on statistical classification. It has applications in telemedicine, virtual reality, computer games, and sign language studies. The focus is placed on (1) how to select an appropriate set of postures having a satisfactory level of discrimination power, and (2) comparison of geometric and moment invariant propertie...