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\iteman{io-port 05978795}
\itemau{Pusiol, Guido; Bremond, Francois; Thonnat, Monique}
\itemti{Unsupervised discovery, modeling, and analysis of long term activities.}
\itemso{Crowley, James L. (ed.) et al., Computer vision systems. 8th international conference, ICVS 2011, Sophia Antipolis, France, September 20--22, 2011. Proceedings. Berlin: Springer (ISBN 978-3-642-23967-0/pbk). Lecture Notes in Computer Science 6962, 101-111 (2011).}
\itemab
Summary: This work proposes a complete framework for human activity discovery, modeling, and recognition using videos. The framework uses trajectory information as input and goes up to video interpretation. The work reduces the gap between low-level vision information and semantic interpretation, by building an intermediate layer composed of Primitive Events. The proposed representation for primitive events aims at capturing meaningful motions (actions) over the scene with the advantage of being learned in an unsupervised manner. We propose the use of Primitive Events as descriptors to discover, model, and recognize activities automatically. The activity discovery is performed using only real tracking data. Semantics are added to the discovered activities (e.g., ``Preparing Meal'', ``Eating'') and the recognition of activities is performed with new datasets.
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\itemli{doi:10.1007/978-3-642-23968-7\_11}
\end