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This paper describes a road obstacle classification system that recognizes both vehicles and pedestrians in far-infrared images. Different local and global features based on Speeded Up Robust Features (SURF) were investigated and then selected in order to extract a discriminative signature from the infrared spectrum. First, local features representing the local appearance of an obstacle, are extracted...
The detection of an obstacle in a traffic scene situation (obstacle which most often means a pedestrian or a vehicle) is a real challenge due to the outdoor environment and the variety of appearance of the obstacle. In this paper some details about our recognition module applied on visible and infrared image databases are presented. Given an image, or a region within an image, generate different types...
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