Understanding transit scenes: a survey on human behavior-recognition algorithms
IEEE Transactions on Intelligent Transportation Systems
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When evaluating the performance of a computer-based visual tracking system one often wishes to compare results with a standard human observer. It is a natural assumption that humans fully understand the relatively simple scenes we subject our computers to and because of this, two human observers would draw the same conclusions about object positions, tracks, size and even simple behaviour patterns. But is that actually the case? This paper provides a baseline for how computer-based tracking results can be compared to a standard human observer.