Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
A revaluation of frame difference in fast and robust motion detection
Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks
Efficient wavelet based detection of moving objects
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Real-time foreground-background segmentation using codebook model
Real-Time Imaging
Statistical modeling of complex backgrounds for foreground object detection
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
The Undecimated Wavelet Decomposition and its Reconstruction
IEEE Transactions on Image Processing
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In real-world surveillance systems, where variation of light and camera parameters can sometimes severely impair the normal operation of background subtraction algorithms, better results are obtained with differencing schemes. We have earlier demonstrated that differencing of detail images produced by wavelet transformation can lead to more stable detection results. In this paper, we considerably extend that framework, by introducing the modified z-scores calculated from wavelet coefficient differences. Foreground pixels are detected as outliers in normal distribution by modified z-score test. The threshold value used in the outlier test is optimized by maximizing the precision and recall measures on several training frames. Finally, the elimination of ghosts from motion detection is done by double modified z-score testing, that is similar in idea to double frame differencing. The resulting motion detection method shows considerable resilience to changes in illumination and camera parameters and also produces a lower amount of detection errors than other motion detection methods.