Fast Calculation of Histogram of Oriented Gradient Feature by Removing Redundancy in Overlapping Block

In order to improve pedestrian detection accuracy, histogram of oriented gradient (HOG) feature is widely used in many applications. Although HOG feature can provide high detection accuracy, fast detection time is hardly achieved due to its computational complexity. Therefore, this paper describes a novel algorithm for fast calculation of HOG feature. In the proposed algorithm, HOG feature is calculated based on cells instead of overlapping blocks to avoid redundancy. Furthermore, by identifying key rules and sharing common operations in trilinear interpolation, the number of required operations in HOG feature calculation is reduced up to 60.5% while detection accuracy is not degraded at all. Therefore, the proposed method is applicable to many applications such as intelligent vehicles, robots, and surveillance systems in which both high detection rate and fast detection time are strongly required.