Abstract
Increasingly computer vision discipline needs annotated video databases to realize assessment tasks. Manually providing ground truth data to multimedia resources is a very expensive work in terms of effort, time and economic resources. Automatic and semi-automatic video annotation and labeling is the faster and more economic way to get ground truth for quite large video collections. In this paper, we describe a new automatic and supervised video annotation tool. Annotation tool is a modified version of ViPER-GT tool. ViPER-GT standard version allows manually editing and reviewing video metadata to generate assessment data. Automatic annotation capability is possible thanks to an incorporated tracking system which can deal the visual data association problem in real time. The research aim is offer a system which enables spends less time doing valid assessment models.
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Serrano, M.A., Gracía, J., Patricio, M.A., Molina, J.M. (2010). Interactive Video Annotation Tool. In: de Leon F. de Carvalho, A.P., Rodríguez-González, S., De Paz Santana, J.F., Rodríguez, J.M.C. (eds) Distributed Computing and Artificial Intelligence. Advances in Intelligent and Soft Computing, vol 79. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14883-5_42
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DOI: https://doi.org/10.1007/978-3-642-14883-5_42
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