Abnormal Motion Detection in a Real-Time Smart Camera System

Mona Akbarniai Tehrani, Richard Kleihorst, Peter Meijer, Lambert Spaanenburg

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

9 Citations (SciVal)


This paper discusses a method for abnormal motion detection and its real-time implementation on a smart camera. Abnormal motion detection is a surveillance technique that only allows unfamiliar motion patterns to result in alarms. Our approach has two phases. First, normal motion is detected and the motion paths are trained, building up a model of normal behaviour. Feed-forward neural networks are here used for learning. Second, abnormal motion is detected by comparing the current observed motion to the stored model. A complete demonstration system is implemented to detect abnormal paths of persons moving in an indoor space. As platform we used a wireless smart camera system containing an SIMD (Single. Instruction Multiple-Data) processor for real-time detection of moving persons and an 8051 microcontroller for implementing the neural network. The 8051 also functions as camera host to broadcast abnormal events using Zig Bee to a main network system.
Original languageEnglish
Title of host publicationThird ACM/IEEE International Conference on Distributed Smart Cameras, 2009. ICDSC 2009
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)978-1-4244-4620-9
Publication statusPublished - 2009
Event3rd ACM/IEEE International Conference on Distributed Smart Cameras - Como, Italy
Duration: 2009 Aug 302009 Sep 2


Conference3rd ACM/IEEE International Conference on Distributed Smart Cameras

Subject classification (UKÄ)

  • Electrical Engineering, Electronic Engineering, Information Engineering


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