Paper
Adaptive Decision Support Technique for Machine Vision-Based Security Systems to Detect Anomalous Events
- Authors:
- Aaron R. Rababaah
- Abstract
- There is an increasing interest in visual surveillance geared toward improving security and safety in various environments and this has led to numerous researches in the field of machine vision in areas that include people tracking, human activity recognition and crowded behaviour analysis. While these researches have been largely successful in provided theoretical framework for solving a broad set of problems in visual surveillance, they have not been largely implemented in designing an automated surveillance system deployed in a variety of real-world surveillance environment. This work designed and implemented an automatic indoor visual surveillance system for facility security applications. The video surveillance system was developed and implemented in Matlab with the capability to detect an object in a surveillance environment, track such object, compute object’s features and determines if the tracked object’s activity is normal or abnormal. The designed system performed reliably well, with an accuracy of over 92% and could be further modified and harnessed to for real time video surveillance of a range of indoor facility security applications.
- Keywords
- Machine Vision; Surveillance; Security Systems; Object Tracking; Event Detecion and Classification
- StartPage
- 94
- EndPage
- 103
- Doi