A pedestrian detection method using the extension of the HOG feature

Development of an ITS (Intelligent Transport System) has drawn much attention from computer vision community in recent years. In particular, various techniques for detecting pedestrians automatically have been proposed by many researchers. Among them, the HOG feature proposed by Dalai & Triggs has gained much interest in the pedestrian detection. However, previous methods including the original HOG feature have not achieved satisfactory detection rates. In this paper, we propose an extension of the HOG feature, i.e., flexible choice of the number of bins and automatic definition of a cell size and a block size by parameterizing their scales. By comparative experiments, it was confirmed that the proposed method outperforms the previous methods in the performance of pedestrian detection.SCIS & ISIS 2014, December 3-6, 2014, Kitakyushu International Conference Cente

A Method of Navigating a Visually Impaired Person Using MY VISION

This paper describes a method of navigating a visually impaired person who walks on a sidewalk and goes through a pedestrian crossing by the use of an ego-camera system named MY VISION. The proposed method finds a walkable region on the sidewalk. Thus, at a pedestrian crossing, it finds a traffic light and judges an appropriate timing to cross the road by analyzing the color and flashing status of the signal. The walkable region is found employing Graph- Based Segmentation (GBS), and once a pedestrian crossing is reached through the use of a GPS signal, a traffic light is detected by use of the HOG feature and Random Forest. The effectiveness of the proposed method was verified by experiments. This implies usefulness of a MY VISION syste