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The first part of this chapter introduces a mathematical geometry model which is used to analyze the iso-disparity surface. This model can be used to dynamically adjust the positions, poses and baseline lengths of multiple stereo pairs of cameras in 3D space in order to get sufficient visibility and accuracy for surveillance, tracking and 3D reconstruction. The depth reconstruction accuracy is quantitatively analyzed by the proposed model. The proposed iso-disparity mathematical model presents possibility of reliable control of the iso-disparity curves’ shapes and intervals by applying the systems configuration and target properties. In the second part of this chapter, the key factors affecting the accuracy of 3D reconstruction are analysed. It shows that the convergence angle and target distance influence the depth reconstruction accuracy most significantly. The depth accuracy constraints are implemented in the model to control the stereo pair’s baseline length, position and pose. It guarantees a certain accuracy in the 3D reconstruction. The reconstruction accuracy is verified by a cubic reconstruction method. The optimization is implemented by applying the camera, object and stereo pair constraints into the integer linear programming.

Arrangement of a Multi Stereo Visual Sensor System for a Human Activities Space