Abstract
The present work aims to exploit the new generation of 3D vision systems for detecting people. We present a challenge process dedicated to test the feasibility of detection over disparity maps by exploiting techniques used with monocular cues, specifically HOG/SVM. Disparity maps are extracted by a developed stereoscopic vision system using two passive sensors with an algorithm stack well adopted to real time constraint with lower processing speeds. This detection module can improve systems' perception ability in complex scenes under shadows, gradual/sudden illumination changes and animated texture. Another key point is to estimate their exact locations to predict intrusions in monitored areas. Results indicate a clear advantage of the proposed method to enhance the rate of performance up to 99.6%.