Distance-Based Descriptors for Pedestrian Detection

In this paper, we propose an improvement of the detection approach that is based on the distance function. In the method, the distance values are computed inside the image to describe the properties of objects. The appropriately chosen distance values are used in the feature vector that is utilized as an input for the SVM classifier. The key challenge is to find the right way in which the distance values should be used to describe the appearance of objects effectively. The basic version of this method was proposed to solve the face detection problem. As we observed from the experiments, the method in the basic form is not suitable for pedestrian detection. Therefore, the goal of this paper is to improve this method, and create the pedestrian detector that outperforms the state-of-the-art detectors. The experiments show that the proposed improvement overcomes the accuracy of the basic version by approximately 10%.

• Type: Journal
• Year: 2015
• Where: ACIVS
• Authors: Radovan Fusek, Eduard Sojka
• Keywords: ACIVS 2015, Computer Vision