Abstract
The content of this article explores the use of 3D face tracking systems by implementing of active stereo vision cameras to ascertain the position of a person's face. The various experiments conducted in-depth have produced both promising and satisfying results for images that have enabled examiners to determine the disparity between images. The paper also explores some of the various challenges researchers are facing with the implementation of algorithms to construct cloud-points in from stereo-based images. The reviewed recommendations suggest on better software components that would avail final 3D computational images or reconstructions that can easily be matched to the original. The tracking system modules address the challenges of the practical application of face tracking including pose illumination and occlusion. The content of the paper evaluates the putting into practice of multi-view or multiple stereo cameras enhance the field of view to improve the performance of a 3D tracking system. Face tracking using functional multi-view stereo camera systems can significantly solve the correspondence problem and the issue of comparing scenes or image points given that extra views reduced ambiguity in matching.