Optimization of Rotation-Invariant Feature Detection Method for Pedestrian Recognition

In the technology of Advanced Safety Vehicle(ASV), it is important elements to detect pedestrians. There is a technique which used image features and a classifier for pedestrian detection. However, pedestrians have pose variations, such as a rotation. That's why we cannot always get the same features. In order to solve this problem, we can use a way which used the rotation-invariant HOG, but this method needs very high costs because it's not optimized for pedestrian detection. Therefore, we improved calculating method of the rotation-invariant HOG for pedestrian detection and compared this proposed method with the conventional method. As a result, recognition rate was turned from 53.75% to 71.7%.