Jan 3, 2020 · The RKBMF model automatically infers the parameters and latent variables including the reduced rank using variational Bayesian inference.

We employ RKBMF to extract background and foreground information from a traffic video. Experimental results demonstrate that RKBMF outperforms state-of-the-art ...

Abstract. Development of effective and efficient techniques for video analysis is an important research area in machine learning and computer vision. Matrix ...

We employ RKBMF to extract background and foreground information from a traffic video. Experimental results demonstrate that RKBMF outperforms state-of-the-art ...

Jan 1, 2019 · Springer Nature Switzerland AG 2019. Development of effective and efficient techniques for video analysis is an important research area in ...

We employ RKBMF to extract background and foreground information from a traffic video. Experimental results demonstrate that RKBMF outperforms state-of-the-art ...

This work proposes to simultaneously exploit the advantages of these two optimizing approaches in a unified framework called Joint Matrix Decomposition and ...

Robust Kernelized Bayesian Matrix Factorization for Video Background/Foreground Separation. 2019 | Book chapter. DOI: 10.1007/978-3-030-37599-7_40.

Robust kernelized Bayesian matrix factorization for video background/foreground separation. HB Xie, C Li, RYD Xu, K Mengersen.

Mergensen, “Robust Kernelized Bayesian Matrix Factorization for Video Background/Foreground Separation”, International Conference on Machine Learning ...