Aiming to solve the change of the extrinsic parameters between the two cameras in free binocular stereo vision system caused by the rotation of the cameras, a method for acquiring the dynamic extrinsic parameters based on calibration of rotation axis was proposed. Multiple rotation and translation matrixes were obtained by the calibration at different positions, then the parameters of rotation axis could be calculated by using least square method. Combined with the intrinsic and extrinsic parameters at initial position and rotation angle, the dynamic extrinsic parameters between the two cameras could be calculated in real time. The chessboard corners were reconstructed with the dynamic extrinsic parameters calculated by the proposed method, the result showed that the average error was 0.241mm and the standard deviation was 0.156mm. Compared with the calibration method based on multiple-plane calibration target, the proposed method is easier to implement and has higher precision, where dynamic extrinsic parameters can be acquired without real-time calibration.

Body parts segmentation of human point-cloud model is an important research content in action recognition and virtual reconstruction fields. Focused on this issue, a multi-constrained segmentation algorithm based on classified skeleton,geodesic distance, feature points and posture analysis was proposed.By generating the classified skeleton and geodesic distance of point-cloud, the roughly segmented point sets of each body part were got. Feature points were positioned by an algorithm depending on geodesic path and optimized by a curve fit method.According to these feature points and some anatomical features of human body, multiple constraints were constructed and roughly segmented point sets were segmented once again.The experimental results demonstrate that the segmentation effects of human point cloud models with different action, size and precision in standing posture are consistent with visual understanding of human. The point-cloud of body parts obtained through this algorithm can be used for posture analysis and so on.