Mirror reflection invariant HOG descriptors for object detection

Histogram of Oriented Gradients (HOG) [1] descriptors have been widely used for object detection. An important limitation is that these descriptors tend to vary considerably when objects are horizontally flipped, as is often the case. We propose novel MI-HOG descriptors that are obtained by transforming HOG descriptors to be invariant to mirror reflection. In their extraction process, we consider not only the transform of independent elements but also the combination of those in different location and in orientation, which yields better performance. We showed a greater than 10 % increase in average precision compared to HOG descriptors.