Object classification with multiresolution wavelet decomposition
Marco Leo, Antonella Branca, Giovanni Attolico, Arcangelo Distante · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2002
The main aim of this work is moving object recognition 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 vehicles and peoples in dynamic scenes. The classification is purely based on the object 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.