Increased complexity of low-level structures improves histograms of compositions

While low-level visual features, such as histogram of oriented gradients (HOG), have been successfully used for object detection and categorization, we have been able to improve upon their performance by introducing histogram of compositions (HoC) in our previous work. In this paper we propose an extended version of HoC descriptor that uses additional layers from hierarchical model. We experimentally show that extended HoC surpasses the performance of the original descriptor by approximately 5% as additional layer provides higher complexity of compositions. Furthermore, with additional layer we show to produce competitive results to original HoC descriptor combined with HOG and can even further increase performance by adding HOG on top of HoC with additional layer.