A Model-Free Voting Approach for Integrating Multiple Cues

Computer vision systems, such as “seeing” robots, aimed at functioning robustly in a natural environment rich on information benefit from relying on multiple cues. Then the problem of integrating these become central. Existing approaches to cue integration have typically been based on physical and mathematical models for each cue and used estimation and optimization methods to fuse the parameterizations of these models.

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