Real-time object detection using segmented and grayscale images

Abstract

This paper describes an approach that performs visual object detection in real-time by combining the strength of processing the color segmented image along with that of the grayscale image of the same scene. This approach was developed with the annual RoboCup Competition in mind, specifically the 4-Legged League where teams of Sony AIBO robots compete in the game of soccer. The images used for processing were taken from the camera located in the head of the robots, and the objects of interest to be detected were the actual AIBO robots. We use color segmented images for producing initial hypotheses for the location of robots in the image, and grayscale images for final classification purposes. Using both representations to process a scene allows each to make up for the deficiencies of the other, and provides a good balance between fast processing time and high detection accuracy. We present our algorithms and show illustrative examples of their performance