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A method of activity detection is described. This technique uses a periodicity measure on gray-level signals extracted along spatio-temporal reference curves. The technique is illustrated using real-world examples of activities. It is shown that the technique robustly detects complex periodic activities, while excluding nonperiodic motion. A technique to recognize these activities using the detection scheme described is proposed. It is not clear how much the periodicity alone is useful for recognition, but the authors believe that the phase information is valuable for activity recognition.>
Polana et al. (Wed,) studied this question.
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