Syed Farooq AliAlizaa FatimaNoman NazarMuhammad MuazFatima Idrees2014-01-082014-01-082013Ali, S. F., Fatima, A., Nazar, N., Muaz, M., & Idrees, F. (2013). Human Fall Detection. Paper presented at the 16 International Multi Topic Conference (INMIC) 2013, University of Engineering and Technology, Lahore 54890, Pakistan.https://escholar.umt.edu.pk/handle/123456789/929Fall-induced injuries are common in the elderly population. Delay or lack of medical care after the occurrence of a fall often results in injuries, sometimes severe, and can also lead to death in some cases. Falls, therefore, are critical occurrences for the elderly. Detecting falls automatically, as they occur, can lead to better timed medical care which can in turn reduce the subsequent medical complications. In this paper we describe an effective fall detection system based on videos dataset generated using multiple cameras. Approach proposed in this paper outperforms in accuracy as compared to the other existing approach. It uses several images descriptors or features which are fed to a number of classifiers to detect falls.enHuman Fall DetectionFixed Camera BasedBackgroundForegroundArticle