Object recognition and cognitive map formation using active stereo vision in a virtual world

In this paper we describe an algorithm for object recognition and cognitive map formation using stereo image data in a 3D virtual world where 3D objects and a robot with stereo imaging system are simulated. Stereo imaging system is simulated so that the actual human visual system properties such as focusing, accommodation, field of view are parameterized. Only the stereo images obtained from this world are supplied to the virtual robot (agent). By applying our disparity algorithm on stereo image pairs, depth map for the current view is obtained. Using the depth information for the current view, a cognitive map of the environment is updated gradually while the virtual agent is exploring the environment. The agent explores its environment in an intelligent way using the current view and environmental map information obtained up to date. Also, during exploration if a new object is observed, from its view from different directions, it is labeled with its shape such as sphere, cylinder, cone

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