Part-Based RDF for Direction Classification of Pedestrians, and a Benchmark

This paper proposes a new benchmark dataset for pedestrian body-direction classification, proposes a new framework for intra-class classification by directly aiming at pedestrian body-direction classification, shows that the proposed framework outperforms a state-of-the-art method, and it also proposes the use of DCT-HOG features (by combining a discrete cosine transform with the histogram of oriented gradients) as a novel approach for defining a random decision forest.