Generation of regions of interest with potential of containing pedestrians through target search by using monocular vision
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http://orcid.org/0000-0001-7507-3325
Bryan Quinga
http://orcid.org/0000-0002-9551-6688
Noemí Onofa
http://orcid.org/0000-0002-4215-509X
Fabián Gallardo
http://orcid.org/0000-0001-6860-9697
Abstract
This article presents an algorithm for regions of interest generation with high potential to contain a pedestrians over monocular images. The generation of these regions has been built using an algorithm to generate search hyperplanes in function of the road-surface together with the generation of random windows on this area plus a variation of the pyramidal sliding window technique; then the pre-processing is done using vertical and horizontal gradient filters. To verify that the region is a possible pedestrian, we start from two hypotheses regarding the human figure, the vertical component is greater than the horizontal and the strong vertical human-symmetry. Through this process, a reduced and optimal set of Regions is obtained in the range of between 2 and 25 meters in front of the camera. The experimental results, over the state of the art databases, show that there is a 91% rate of valid windows with respect to the total of true windows, at 25.38 frames per second.
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