Combining peripheral and foveal humanoid vision to detect, pursue, recognize and act

In this paper we present a humanoid system that can integrate information provided by its foveal and peripheral cameras. We use peripheral vision to detect and pursue objects of interest based on simple shape and color models. A detection event triggers the robot to direct its eyes towards the object, thus making a more detailed analysis of the observed objects in higher resolution foveal images feasible. The recognition is based on principal component analysis and is performed while the robot actively pursues the detected object. The classification results are inferred using information from a video stream rather than just a single image. Once the desired object is recognized, the robot reaches for it while ignoring other objects.