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.
A NOVEL SEGMENTATION METHOD FOR CROWDED SCENES / Bloisi, Domenico Daniele; Iocchi, Luca; D. N., Monekosso; P., Remagnino. - 2:(2009), pp. 484-489. (Intervento presentato al convegno 4th International Conference on Computer Vision Theory and Applications tenutosi a Lisboa; Portugal nel FEB 05-08, 2009).
A NOVEL SEGMENTATION METHOD FOR CROWDED SCENES
BLOISI, Domenico Daniele;IOCCHI, Luca;
2009
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
