Separation of video clips into foreground and background components is a useful and important technique, making recognition, classification and scene analysis more efficient. In this paper, we propose a motion-assisted matrix restoration (MAMR) model for foreground-background separation in video clips. In the proposed MAMR model, the backgrounds across frames are modeled by a low-rank matrix, w...

An online nonnegative matrix factorization (NMF) algorithm based on recursive least squares (RLS) is described in a matrix form, and a simplified algorithm for a low-complexity calculation is developed for frame-by-frame online audio source separation system. First, the online NMF algorithm based on the RLS method is described as solving the NMF problem recursively. Next, a simplified algorithm...

We propose a new sufficient condition for separation of colored source signals with temporal structure, stating that the separation is possible, if the source signals have different higher self-correlation functions of even order. We show that the problem of blind source separation of uncorrelated colored signals can be converted to a symmetric eigenvalue problem of a special covariance matrix ...

Fuzzy c-means (FCM) clustering is based on minimizing the fuzzy within cluster scatter matrix trace but FCM neglects the between cluster scatter matrix trace that controls the distances between the class centroids. Based on the principle of cluster centers separation, fuzzy cluster centers separation (FCCS) clustering is an extended fuzzy c-means (FCM) clustering algorithm. FCCS attaches import...

This paper focuses on underdetermined blind source separation (BSS) of three speech signals mixed in a real environment from measurements provided by two sensors. Underdetermined BSS is a problem that has not yet been intensely studied and so far no satisfying solution has been obtained. The major issue encountered in previous work relates to the occurrence of distortion, which affects a separa...

In this paper, we propose a novel algorithm for underdetermined blind identification problems in blind signal separation. The proposed algorithm is based on the charrelation matrix of observations. The charrelation matrix can not only be considered as a generalized covariance matrix, but also incorporates higher-order information. It is significant for blind separation problem based on statisti...

This paper is a survey on the source separation problem, and on methods used for solving this problem. In a blind context, i.e. without information about the sources but their mutual independence, methods are based on Independent Component Analysis (ICA). On the contrary, using priors on sources, one can developed semi-blind approaches which are very efficient and often much more simpler. Curre...

Audio source separation is a useful preprocessing step for remixing or transcription of music. It can be shown, that the separation quality increases, if the separation algorithm gets additional side information, e.g. the score of the current mixture [5]. In many cases the score of a musical piece is not available and has to be extracted by a professional musician or an automatic music transcri...

In two previous papers, we proposed an audio Informed Source Separation (ISS) system which can achieve the separation of I > 2 musical sources from linear instantaneous stationary stereo (2-channel) mixtures, based on audio signal’s natural sparsity, pre-mix source signals analysis, and side-information embedding (within the mix signal). In the present paper and for the first time, we apply thi...

This paper compares the eigenstructure and modulation algorithms, which are used for two-channel lossless FIR lter optimization. We study the e ects of eigenvalue separation of the input covariance matrix and the step size on their convergence behavior. First, we show that the convergence rate of two algorithms increases as the separation of eigenvalues of the covariance matrix increases. The m...