Intelligent Pedestrian Detection using Optical Flow and HOG
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 9
Abstract
Pedestrian detection is an important aspect of autonomous vehicle driving as recognizing pedestrians helps in reducing accidents between the vehicles and the pedestrians. In literature, feature based approaches have been mostly used for pedestrian detection. Features from different body portions are extracted and analyzed for interpreting the presence or absence of a person in a particular region in front of car. But these approaches alone are not enough to differentiate humans from non-humans in dynamic environments, where background is continuously changing. We present an automated pedestrian detection system by finding pedestrians’ motion patterns and combing them with HOG features. The proposed scheme achieved 17.7% and 14.22% average miss rate on ETHZ and Caltech datasets, respectively.
Authors and Affiliations
Huma Ramzan, Bahjat Fatima, Ahmad Shahid, Sheikh Ziauddin, Asad Safi
Keywords
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- EP ID EP112669
- DOI 10.14569/IJACSA.2016.070955
- Views 111
- Downloads 0
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