歩行者検出における混合正規分布を用いた状態空間の自律構成法

抄録

Recently, Co-occurrence histograms of oriented gradients (CoHOG) describes image features to calculate the co-occurrence of pixels allocated at the local level and has attracted attention as an effective object detection method. However, this method has some problems. For feature descriptions that focus on individual pixels, calculation cost and the number of dimensions tend to increase exponentially with respect to the number of pixels. Multiresolution CoHOG (MRCoHOG) can suppress such exponential increases to linear increase without reducing the classification accuracy. This paper proposes a procedure in which a feature plane is divided using a Gaussian mixture model and a histogram is automatically divided to establish a less costly method for performing MRCoHOG. Experimental results demonstrate that the proposed procedure is more effective than conventional procedures.