We present a novel skin reflectance model for faces and its application to face appearance editing. We decompose the high-dimensional bidirectional scattering surface reflectance distribution function (BSSRDF) of skin into components that can be estimated from measured data. Our model is intuitive, amenable to interactive rendering, and easy to edit. High-quality renderings come close to reprod...

In this paper, we investigate the problem of real-time polyphonic music transcription by employing non-negative matrix factorization techniques and the β-divergence as a cost function. We consider real-world setups where the music signal arrives incrementally to the system and is transcribed as it unfolds in time. The proposed transcription system is addressed with a modified non-negative matri...

the polynomial interpolation in one dimensional space r is an important method to approximate the functions. the lagrange and newton methods are two well known types of interpolations. in this work, we describe the semi inherited interpolation for approximating the values of a function. in this case, the interpolation matrix has the semi inherited lu factorization.

We propose an upper confidence bound for the threshold at which a regression function takes off from its baseline value in a white noise model. The confidence bound is based on multi-scale test statistics which involve combining one-sided kernel estimates with varying bandwidths in a specific manner. The bound is adaptive and near-optimal in the sense that it does require knowing the smoothness...

In this paper, we propose the application of standard decomposition approaches to find local correlations in multimodal data. In a test scenario, we apply these methods to correlate the local shape of turbine blades with their associated aerodynamic flow fields. We compare several decomposition algorithms, i.e., k-Means, Principal Component Analysis, Non-negative Matrix Factorization and Uni-or...

This paper presents a novel mid-level representation for action recognition, named spatio-temporal aware non-negative component representation (STANNCR). The proposed STANNCR is based on action component and incorporates the spatial-temporal information. We first introduce a spatial-temporal distribution vector (STDV) to model the distributions of local feature locations in a compact and discri...

Many recommender systems have only implicit user feedback. The two possible ratings are positive and negative, but only part of positive entries are observed. One-class matrix factorization (MF) is a popular approach for such scenarios by treating some missing entries as negative. Two major ways to select negative entries are by sub-sampling a set with similar size to that of observed positive ...

A model for localized key finding from audio is proposed. Besides being able to estimate the key in which a piece starts, the model can also identify points of modulation and label multiple sections with their key names throughout a single piece. The front-end employs an adaptive tuning stage prior to spectral analysis and calculation of chroma features. The segmentation stage uses groups of co...