Task Oriented Vision

In this paper, we introduce a systematic approach for tailoring perceptual modules to specific tasks. In this approach, modules for image segmentation, object representation, and manipulation are selected based on the constraints of the target task and on the environment. The goal is to generate the most efficient set of perceptual modules based on the constraints. This approach is a high-level equivalent to the more traditional low-level active control of sensing strategies. We illustrate this approach through two example systems. In the first system, the task is to manipulate natural objects. In the second system, the task is to pick industrial parts out of a bin. We show how the two tasks were decomposed and analyzed to yield the best match between perceptual capabilities and task requirements. Then, we introduce a general framework for task-based development of vision systems.

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