Pedestrian detection of road scenes using depth and intensity features

Abstract

In this paper, we present pedestrian detection method using fusion of intensity and depth features. Complementary fusion of these features significantly boosts the detection performance. Histogram of Oriented gradient (HOG) is applied for feature extraction in both intensity and depth images and trained by linear SVM. Our approach has an advantage over the conventional intensity image based methods, since depth features are robust against illumination, complex background and human pose variations. The experimental result shows that our proposed method has better detection performance.