Abstract
Falls are major causes of mortality and morbidity in the elderly. The existing CCD-camera based solutions require time for installation, camera calibration and are not generally cheap. In this paper we show how to achieve automatic fall detection using Kinect sensor. The person is segmented on the basis of the updated depth reference images. Afterwards, the distance of the person to the ground plane is calculated. The ground plane is extracted by the RANSAC algorithm. The point cloud belonging to the floor is determined using v-disparity images and the Hough transform.
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Kepski, M., Kwolek, B. (2013). Human Fall Detection Using Kinect Sensor. In: Burduk, R., Jackowski, K., Kurzynski, M., Wozniak, M., Zolnierek, A. (eds) Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013. Advances in Intelligent Systems and Computing, vol 226. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00969-8_73
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DOI: https://doi.org/10.1007/978-3-319-00969-8_73
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