Automatic Detection of Human Fall in Video

  • Vinay Vishwakarma
  • Chittaranjan Mandal
  • Shamik Sural
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4815)


In this paper, we present an approach for human fall detection, which has important applications in the field of safety and security. The proposed approach consists of two parts: object detection and the use of a fall model. We use an adaptive background subtraction method to detect a moving object and mark it with its minimum-bounding box. The fall model uses a set of extracted features to analyze, detect and confirm a fall. We implement a two-state finite state machine (FSM) to continuously monitor people and their activities. Experimental results show that our method can detect most of the possible types of single human falls quite accurately.


Video Clip Gaussian Mixture Model Object Detection Vertical Gradient Finite State Machine 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Vinay Vishwakarma
    • 1
  • Chittaranjan Mandal
    • 1
  • Shamik Sural
    • 1
  1. 1.School of Information Technology, Indian Institute of Technology, KharagpurIndia

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