Real-Time Object Detection for "Smart" Vehicles

This paper presents an e cient shape-based object detection method based on Distance Transforms and describes its use for real-time vision on-board vehicles. The method uses a template hierarchy to capture the variety of object shapes; e cient hierarchies can be generated o ine for given shape distributions using stochastic optimization techniques i.e. simulated annealing. Online, matching involves a simultaneous coarse-to- ne approach over the shape hierarchy and over the transformation parameters. Very large speedup factors are typically obtained when comparing this approach with the equivalent brute-force formulation; we have measured gains of several orders of magnitudes. We present experimental results on the real-time detection of tra c signs and pedestrians froma moving vehicle. Because of the highly time sensitive nature of these vision tasks, we also discuss some hardwarespeci c implementationsof the proposed method as far as SIMD parallelism is concerned.

• Type: Conference
• Year: 1999
• Where: ICCV
• Authors: Dariu Gavrila, Vasanth Philomin
• Keywords: Computer Vision, ICCV 1999, Object Detection Method, Stochastic Optimization Techniques, Vision On-board Vehicles