Expected Confusion as a Method of Evaluating Recognition Techniques
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We derive an expected confusion metric, as opposed to reporting percent correct with a limited database, as a method to evaluate recognition techniques. This metric allows us to predict how well a given feature vector will filter identity in a large population. Our expected confusion is the ratio of the average individual variation of a feature vector to that of the population variation of the feature vector. We evaluate our gait-recognition technique [2] that recovers static body and stride parameters of walking subjects with the expected confusion metric to demonstrate its use.
[1] Aaron F. Bobick,et al. A Multi-view Method for Gait Recognition Using Static Body Parameters , 2001, AVBPA.
[2] Thomas M. Cover,et al. Elements of Information Theory , 2005 .