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We investigate the problem of automatically determining what type of shoe left an impression found at a crime scene. This recognition problem is made difficult by the variability in types of crime scene evidence (ranging from traces of dust or oil on hard surfaces to impressions made in soil) and the lack of comprehensive databases of shoe outsole tread patterns. We find that mid-level features extracted...
Active learning is a useful tool for in-situ learning and adaptive classification systems. While traditional active learning is focused mostly on the single-sample mode, the batch mode of active learning is more interactions efficient. This paper proposes a computationally efficient approach for maximizing the joint entropy of a batch of samples and thereby attaining the maximal information gain and...
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