A NOVEL SEGMENTATION METHOD FOR CROWDED SCENES
Domenico D. Bloisi, Luca Iocchi, Dorothy Monekosso, Paolo Remagnino · 2009
Video surveillance is one of the most studied application in Computer Vision. We propose a novel method to identify and track people in a complex environment with stereo cameras. It uses two stereo cameras to deal with occlusions, two different background models that handle shadows and illumination changes and a new segmentation algorithm that is effective in crowded environments. The algorithm is able to work in real time and results demonstrating the effectiveness of the approach are shown.