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Activity Recognition and Classification

In the past years, the field of human activity recognition has grown dramatically, reflecting its importance in many high-impact societal applications including smart surveillance, web-video search and retrieval, quality-of-life devices for elderly people, and human-computer interfaces. Given the initial success of bag-of-words methods for action classification, the field is gradually moving towards more structured interpretation of complex human activities involving multiple people and objects as well as interactions among them in various realistic scenarios. New important research topics and problems are appearing as a consequence, including (i) modeling temporal structure of activities, (ii) learning relations between actions and objects/scenes/social roles, (iii) group activity recognition, and  (iv) first-person activity recognition. The objective of this tutorial is to introduce and overview recent progress in these emerging topics, as well as to discuss, motivate and encourage future research in diverse subfields of action recognition.