Pedestrian Detection from a Moving Vehicle

Abstract. This paper presents a prototype system for pedestrian detection on-board a moving vehicle. The system uses a generic two-step approach for efficient object detection. In the first step, contour features are used in a hierarchical template matching approach to efficiently "lock" onto candidate solutions. Shape matching is based on Distance Transforms. By capturing the objects shape variability by means of a template hierarchy and using a combined coarse-to-fine approach in shape and parameter space, this method achieves very large speed-ups compared to a brute-force method. We have measured gains of several orders of magnitude. The second step utilizes the richer set of intensity features in a pattern classification approach to verify the candidate solutions (i.e. using Radial Basis Functions). We present experimental results on pedestrian detection off-line and on-board our Urban Traffic Assistant vehicle and discuss the challenges that lie ahead.

• Type: Conference
• Year: 2000
• Where: ECCV
• Authors: Dariu Gavrila
• Keywords: Computer Vision, ECCV 2000, Generic Two-step Approach, Objects Shape Variability, Pattern Classification Approach, Pedestrian Detection Off-line, Template Matching Approach