LOcal Binary Similarity segmenTER (LOBSTER)
LOBSTER (P. St-Charles, LITIV, Canada)
P. St-Charles, G. Bilodeau, "Improving background subtraction using Local Binary Similarity Patterns," IEEE Winter Conference on Applications of Computer Vision, WACV 2014, pages 509-515, 2014.
Self-Balanced SENsitivity SEgmenter (SuBSENSE)
SuBSENSE (P. St-Charles, LITIV, Canada)
P. St-Charles, G. Bilodeau, R. Bergevin, "Flexible Background Subtraction with Self-Balanced Local Sensitivity", IEEE Change Detection Workshop, CDW 2014, June 2014.
P. St-Charles, G. Bilodeau, R. Bergevin, “SuBSENSE: A Universal Change Detection Method with Local Adaptive Sensitivity”, IEEE Transactions on Image Processing, 2014.
Pixel-based Adaptive Word Consensus Segmenter (PAWCS)
PAWCS (P. St-Charles, LITIV, Canada)
P. St-Charles, G. Bilodeau, R. Bergevin, “A Self-Adjusting Approach to Change Detection Based on Background Word Consensus", IEEE Winter Conference on Applications of Computer Vision, WACV 2015, 2015.
P. St-Charles, G. Bilodeau, R. Bergevin, "Universal Background Subtraction Using Word Consensus Models", IEEE Transactions on Image Processing, Volume 25, No. 10, pages 4768-4781, October 2016.