Support vector machines and Gabor kernels for object recognition on a humanoid with active foveated vision

Object recognition requires a robot to perform a number of nontrivial tasks such as finding objects of interest, directing its eyes towards the objects, pursuing them, and identifying the objects once they appear in the robot´s central vision. We have recently developed a recognition system on a humanoid robot, which makes use of foveated vision to accomplish these tasks (A Ude, et al., 2003). In this paper we present several substantial improvements to this system. We present a biologically motivated object representation scheme based on Gabor kernel functions and show how to employ support vector machines to identify known objects in foveal images based on this representation. A mechanism for visual search is integrated into the system to find objects of interest in peripheral images. The framework also includes a control scheme for eye movements, which are directed using the results of attentive processing in peripheral images.