People detection in dynamic images
Antonella Branca, Marco Leo, Giovanni Attolico, A. Distante · 2003
The main aim of this work is people detection in outdoor environments in the context of video surveillance for intruder detection in archeological sites. Our goal is to propose an example-based learning technique to detect people in dynamic scenes. The classification is purely based on the people shape and not on its image content. First motion information is used for detecting the objects of interest. Haar wavelets are used to represent the images and, finally, a supervised three layer neural network is used to classify the patterns.