Person Surveillance Using Visual and Infrared Imagery

This paper presents a methodology for analyzing multimodal and multiperspective systems for person surveillance. Using an experimental testbed consisting of two color and two infrared cameras, we can accurately register the color and infrared imagery for any general scene configuration, expanding the scope of multispectral analysis beyond the specialized long-range surveillance experiments of previous approaches to more general scene configurations common to unimodal approaches. We design an algorithmic framework for detecting people in a scene that can be generalized to include color, infrared, and/or disparity features. Using a combination of a histogram of oriented gradient (HOG) feature-based support vector machine and size/depth-based constraints, we create a probabilistic score for evaluating the presence of people. Using this framework, we train person detectors using color stereo and infrared stereo features as well as tetravision-based detectors that combine the detector outpu...

• Type: Journal
• Year: 2008
• Where: TCSV
• Authors: Stephen J. Krotosky, Mohan M. Trivedi
• Keywords: Color, General Scene Configurations, Infrared, TCSV 2008