A Bayesian Computer Vision System for Modeling Human Interactions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Direct search methods: then and now
Journal of Computational and Applied Mathematics - Special issue on numerical analysis 2000 Vol. IV: optimization and nonlinear equations
Real-Time Detection of Anomalous Objects in Dynamic Scene
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Fast Simplex Optimization for Active Appearance Model
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
An eigenbackground subtraction method using recursive error compensation
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
Hi-index | 0.00 |
The Eigenbackground model is often stated to perform better than pixel-based methods when illumination variations occur. However, it has originally one demerit, that foreground objects must be small. This paper presents an original improvement of the Eigenbackground model, dealing with large and fast moving foreground objects. The method generates background images using the Nelder-Mead Simplex algorithm and a dynamic masking procedure. Experiments show that the proposed method performs as well as the state-of-the-art Eigenbackground improvements in the case of slowly moving objects, and achieves better results for quickly moving objects.