Machine learningVideo segmentation
Background Subtraction
Background subtraction is a video processing technique that separates moving foreground objects from a static or slowly changing background by comparing each frame to a learned or estimated background model. Widely used in video surveillance and motion detection, background subtraction enables robust foreground detection even in complex scenes with illumination changes.
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Sources
- Stauffer, C., & Grimson, W. E. L. (1999). Adaptive background mixture models for real-time tracking. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 246–252. DOI: 10.1109/CVPR.1999.784637 ↗
- KaewTraKulPong, P., & Bowden, R. (2002). An improved adaptive background mixture model for real-time tracking with shadow detection. Proceedings of the European Conference on Computer Vision (ECCV), 135–144. link ↗