NEW SYMMETRY PEAK PROCESSING AND GA-BASED SVM ALGORITHM FOR PEDESTRIAN DETECTION

Quoc Dinh Truong, Quoc Bao Truong

Abstract


In this paper, we consider the problem of pedestrian detection using a two-stage vision-based approach. The first stage is hypothesis generation (HG), in which potential pedestrian are hypothesized. We proposed a method called “colors difference” to determine the leg position of pedestrian. Then a new symmetry peaks processing is performed to define how many pedestrians are covered in one potential candidate region. The second stage is hypothesis verification (HV). In this stage, all hypotheses are verified by the combination between Decision Tree and a Modified Adaptive Genetic Algorithm to find the best features subset based on Haar-like feature and an appropriate parameters set of Support Vector Machine for classification. Our methods have been tested on different real road images and show very good performance.




DOI: https://doi.org/10.15625/0866-708X/49/5/1895 Display counter: Abstract : 42 views. PDF (Tiếng Việt) : 20 views.

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Published by Vietnam Academy of Science and Technology