Background extraction with a coarse to fine approach

Outline Pixel approach Block-based approach Gaussian mixture model Algorithm description Block-based approach Two level classification Experimental results

Background extraction constraints Depend on the application Real-time Real environment Shadows Illumination changes Background object displacements …

Outline Pixel approach Block-based approach Gaussian mixture model Algorithm description Block-based approach Two level classification Experimental results

Gaussian mixture model [Stauffer & Grimson, ’99] Color at each pixel location is described by a mixture of K Gaussians. Mean, variance and relative weight of each Gaussian are updated according to observations and a learning rate. Good model for illumination changes.

R-D Optimized Policy (1) [Chou & Miao, ’01] Algorithm description [Harville et al., ’01] R-D Optimized Policy (1) [Chou & Miao, ’01] Work in YUV space (reduce shadow misclassification). Determine for each pixel the Gaussian that matches its value best. (on-line K-means approximation). Threshold criterion is used to determine if the matched Gaussian corresponds to the background.

Outline Pixel approach Block-based approach Gaussian mixture model Algorithm description Block-based approach Two level classification Experimental results

R-D Optimized Policy (1) [Chou & Miao, ’01] Two level classification R-D Optimized Policy (1) [Chou & Miao, ’01] First, classify at the block level using a proportion criterion. No parameter updates at this point. Second, use the pixel approach for the regions not classified as background after the first step.

Experimental results Typical values: K= 3, Initial variance = 100, Threshold = 0.4, Alpha (learning rate) = 0.006, Block size = 16, Threshold = Block size.

Conclusion Current block based approach can be faster with the same visual quality. Future work could “dissociate” pixel level and block level completely. Still an open problem.

Acknowledgments Michael Harville Susie Wee John Apostolopoulos

Background extraction with a coarse to fine approach Questions ?