Learning Task-Specific Object Recognition and Scene Understanding

In this paper, we present an approach to object recognition and scene understanding which integrates low-level image processing and high-level knowledge-based components. A novel machine learning system is presented which is used to acquire knowledge relating to a specific task. Learned feedback from high-level to low-level processes is introduced as a means of achieving robust task-specific segmentation. The system has been implemented and trained on a number of scenarios with differing tasks from which results are presented and discussed.

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