Pedestrian Validation in Infrared Images by Means of Active Contours and Neural Networks. (10th May 2010)

• Record Type: Journal Article
• Authors: Bertozzi Bertozzi, Massimo Massimo; Cerri Cerri, Pietro Pietro; Felisa Felisa, Mirko Mirko; Ghidoni Ghidoni, Stefano Stefano; Del Rose Del Rose, Michael Michael
• Other Names: Ives Ives Robert W. Robert W. Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2010(2010)
• Publication Date: 2010-05-10
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2010/752567
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : 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.