Actionlets and Activity Prediction

The increasing ubiquitousness of multimedia information in today's world has positioned video as a favored information vehicle, and given rise to an astonishing generation of social media and surveillance footage. One important problem that will significantly enhance semantic-level video analysis is activity understanding, which aims at accurately describing video contents using key semantic elements, especially activities. We notice that in case a time-critical decision is needed, there is a potential to utilize the temporal structure of videos for early prediction of ongoing human activity.

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