Moving Object Tracking in Intelligent Video Surveillance System
Through the in-depth study of the current motion detection and tracking technologies, combined with the practical application of intelligent video surveillance, this paper improves the existing motion detection and tracking algorithm. The improved algorithm continues the characteristics of original algorithm such as simple to implement and lower computational complexity, increases its range of application and improves the anti-jamming capability and robustness of video tracking.
KeywordsIntelligent surveillance Motion detection Object tracking Camshift Frame difference
- 1.Collins R et al (2000) A system for video surveillance and monitoring. Carnegie Mellon Univ Tech Rep 73:245–252Google Scholar
- 2.Hu W, Tan T, Wang L, Maybank S (2004) A survey on visual surveillance of object motion and behaviors. IEEE Trans SMC 34:334–352Google Scholar
- 5.Han B, Comaniciu D, Davis L (2004) Sequential kernel density approximation through mode propagation: applications to background modeling. ACCV: Asian conference computer vision, vol 15(03), pp 22–27Google Scholar
- 6.Alexandropoulos T, Loumos V, Kayafas E (2004) A Block clustering technique for real-time object detection on a static background, 2nd International IEEE conference on intelligent systems, vol 23(1), pp 169–173Google Scholar
- 8.Power PW, Schoonees JA (2002) Understanding background mixture models for foreground segmentation. Proceeding image and vision computing, New Zealand 11(06):267–271Google Scholar