An approach based on particle swarm optimization for fast object detection

This paper describes a new object detection approach using particle swarm optimization (PSO). The approach is based on the idea that the task of finding a well-matched subwindow (object) can be formulated as an integer nonlinear optimization problem (INOP). We use PSO to solve this formulated INOP. Experiments in the domain of face detection are presented and the results show the effectiveness of the proposed method.