Gradient-DCT (G-DCT) descriptors

Many feature-based object detectors have shown that the use of gradient image information can be a very efficient way to describe the appearance of objects. Especially, the gradient sizes, directions and histograms are commonly used. In this area, the histogram of oriented gradients (HOG) is considered as the state-of-the-art method. The histograms and gradient orientations are used to encode the gradient information in HOG. Nevertheless, many works have proved that the feature vector dimensionality of HOG can be reduced; particularly, the information of the gradient directions is redundant and it can be reduced. This was the motivation to encode the gradient information with the least possible redundant information. In this paper, we propose the method in which the discrete cosine transform (DCT) is used to effectively encode the gradient information; using DCT, the gradient information can be encoded with a relatively small set of DCT coefficients in which the most important gradient information is preserved. We show the properties of presented method for the case of solving the problem of face and pedestrian detection.