3D Body Reconstruction for Immersive Interaction
AMDO '02 Proceedings of the Second International Workshop on Articulated Motion and Deformable Objects
Gesture and Posture Estimation by Using Locally Linear Regression
AMDO '02 Proceedings of the Second International Workshop on Articulated Motion and Deformable Objects
Inference of Human Postures by Classification of 3D Human Body Shape
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
A real-time model-based human motion tracking and analysis for human computer interface systems
EURASIP Journal on Applied Signal Processing
3D Human Motion Reconstruction Using Video Processing
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
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This paper proposes a new real-time method for estimating human postures in 3D from trinocular images. In this method, an upper body orientation detection and a heuristic contour analysis are performed on the human silhouettes extracted from the trinocular images so that representative points such as the top of the head can be located. The major joint positions are estimated based on a genetic algorithm based learning procedure. 3D coordinates of the representative points and joints are then obtained from the two views by evaluating the appropriateness of the three views. The proposed method implemented on a personal computer runs in real-time. Experimental results show high estimation accuracies and the effectiveness of the view selection process.