PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Object-Wise Multilayer Background Ordering for Public Area Surveillance
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
A Robust and Efficient Approach for Human Tracking in Multi-camera Systems
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
Object detection using local difference patterns
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
Towards robust object detection: integrated background modeling based on spatio-temporal features
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part I
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Detection of moving objects is a fundamental task in video based surveillance and security applications. Many detection systems use background estimation methods to model the observed environment. In outdoor surveillance, moving backgrounds (waving trees, clutter) and illumination changes (weather changes, reflections, etc.) are the major challenges for background modelling and the development of a single model that fulfils all these requirements is usually not possible. In this paper we present a background estimation technique for motion detection in non-static backgrounds that overcomes this problem. We introduce an enhanced background estimation architecture with a long-term model and a short-term model. Our system showed that fusion of the detections of these two complementary approaches, improves the quality and reliability of the detection results.