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The database consists of falls and activities of daily living performed by two persons (person1 and person2) – each person performed all activities twice. Hence, the database consists of 72 video sequences, containing 40 falls and 32 activities of daily living. The different scenarios are adopted from Noury et al. [1] and are described in [2].
\n\nUse
\n\nThe dataset is freely available for non-commercial research use. Please also cite our paper [2] when using the dataset for your research.
\n\nReferences
\n\n[1] N. Noury, A. Fleury, P. Rumeau, a K. Bourke, G. O. Laighin, V. Rialle, and J. E. Lundy, “Fall detection – principles and methods.,” in Engineering in Medicine and Biology Society, 2007, vol. 2007, pp. 1663–1666.
\n\n[2] Planinc R., Kampel M., “Robust Fall Detection by Combining 3D Data and Fuzzy Logic”, ACCV Workshop on Color Depth Fusion in Computer Vision, Daejeon, Korea, pp. 121-132, November 2012.
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\n\nWe are devoted to both basic and applied research in the field of Computer Vision or in other words: We are teaching computers to “see”. Computer Vision comprehends the natural world through images, image sequences, and films and reconstructs its properties, such as shape, illumination, and color distributions.
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