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

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9009)

Abstract

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.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.The .enpeda.. ProjectTamaki Campus, The University of AucklandAucklandNew Zealand

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