Chen, T., Sahli, H., Zhang, Y., & Yang, T. (2018). Improved compressive tracking based on pixel-wise learner. Journal of Electronic Imaging. https://doi.org/10.1117/1.JEI.27.1.013003

@article{99c89ff5cd5b476b9d569a84e263b0c8,
title = "Improved compressive tracking based on pixel-wise learner",
abstract = "This work extends upon state-of-the-art multi-scale tracking based on compressive sensing (CT) by increasing the overall tracking accuracy. A pixel-wise classification stage is incorporated in CT-based tracker to obtain relatively stable appearance model, by distinguishing object pixels from the background. Additionally, we identify potential distracting regions which are used in a feedback strategy to handle occlusion and avoid drifting toward nearby regions with similar appearances. We evaluate our approach on several benchmark datasets to demonstrate its effectiveness with respect to state-of-the-art tracking algorithms.",
keywords = "Compressive tracking, Random projection, Pixel-wise learner, Feedback strategy",
author = "Ting Chen and Hichem Sahli and Yanning Zhang and Tao Yang",
year = "2018",
month = jan,
doi = "10.1117/1.JEI.27.1.013003",
language = "English",
journal = "Journal of Electronic Imaging",
issn = "1017-9909",
publisher = "SPIE",
}