Pedestrian Validation in Infrared Images by Means of Active Contours and Neural Networks

Autor: Ghidoni Stefano, Del Rose Michael, Bertozzi Massimo, Cerri Pietro, Felisa Mirko
Jazyk: angličtina
Rok vydání: 2010
Předmět:
Zdroj: EURASIP Journal on Advances in Signal Processing, Vol 2010, Iss 1, p 752567 (2010)
Druh dokumentu: article
ISSN: 1687-6172
1687-6180
Popis: This paper presents two different modules for the validation of human shape presence in far-infrared images. These modules are part of a more complex system aimed at the detection of pedestrians by means of the simultaneous use of two stereo vision systems in both far-infrared and daylight domains. The first module detects the presence of a human shape in a list of areas of attention using active contours to detect the object shape and evaluating the results by means of a neural network. The second validation subsystem directly exploits a neural network for each area of attention in the far-infrared images and produces a list of votes.
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