A Two Phase Genetic Programming Approach to Object Detection

Mengjie Zhang, Peter Andreae, Urvesh Bhowan

Abstract: This paper describes two innovations that improve the efficiency and effectiveness of a genetic programming approach to object detection problems. The first innovation is to break the GP search into two phases with the first phase applied to a selected subset of the training data, and a simplified fitness function. The second phase is initialised with the programs from the first phase, and uses the full set of training data to construct the final detection programs. The second innovation is to add a program size component to the fitness function. Application of this approach to three object detection problems indicated that the innovations increased both the effectiveness and the efficiency of the genetic programming search.