From NOMAD to explorer: active object recognition on mobile robots

Abstract This paper demonstrates the importance of active behavior in machine vision systems. It proposes using activity of the observer for object finding and recognition. The presented robotic system is based on active and qualitative vision approaches which are supplemented by a hierarchical, multiresolution image representation and a parallel implementation of the active vision algorithms. The system uses a hierarchical search strategy to locate and then identify objects in a three-dimensional space. The paper describes the recognition algorithm and its parallel implementation on the SFU hybrid pyramid vision machine. We also introduce a new method for depth recovery—Stereo from Head and Body Movements (SHABM). As shown in our analysis and experiment, it provides a practical and economic means of 3-D sensing on ordinary (wheeled) mobile robots.

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