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Advanced Rotation-Invariant Feature Detection Method for Pedestrian Recognition
Toshiki Yahiro,Kousuke Matsushima 대한전자공학회 2017 대한전자공학회 학술대회 Vol.2017 No.1
In the technology of Advanced Safety Vehicle (ASV), pedestrian detection is an important element. There are techniques using image features and classifiers, but pedestrian regions often include various poses such as rotation. That’s why we cannot always get similar feature values for the same features. The rotation-invariant Histogram of Oriented Gradients(RI-HOG) is a candidate to solve this problem, but this method is not highly accurate because it is not optimized for pedestrian detection. Accordingly, we improved calculating method of the RI-HOG for pedestrian detection and compared this proposed method with the conventional method. As a result, recognition rate was turned from 57.50% to 89.56%.