Abstract
The development of distributed computer vision algorithms promises to significantly advance the state of the art in computer vision systems by improving their efficiency and scalability (through the efficient integration of local information with global optimality guarantees) as well as their robustness to outliers and node failures (because of the use of redundant information). However, in order for this promise to be fulfilled, a number of fundamental challenges to the existing technology in computer vision, distributed optimization, and wireless sensor networks (WSNs) must be addressed.
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