Multilinear Analysis of Image Ensembles: TensorFaces

Vasilescu, M. Alex O.; Terzopoulos, Demetri

doi:10.1007/3-540-47969-4_30

Cited by 606 publications

(518 citation statements)

References 11 publications

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“…The Tucker decomposition and its variations have already found many applications, for example, in signal processing [13], extended Wiener filters [14], face recognition using Tensor-Faces [15], analysis of multi-channel EEG and MEG data [16]. A particular case of the constrained Tucker decomposition is the DEDICOM (DEcomposition into DIrectional COMponents) model [17,18] which allows to analyze asymmetric relationships between groups (objects).…”

Section: Introductionmentioning

confidence: 99%

Extended HALS algorithm for nonnegative Tucker decomposition and its applications for multiway analysis and classification

Phan

Cichocki

2011

Neurocomputing

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Section: Introductionmentioning

confidence: 99%

Extended HALS algorithm for nonnegative Tucker decomposition and its applications for multiway analysis and classification

Phan

Cichocki

2011

Neurocomputing

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“…In [36], [37] and [38] , multi-expression faces were arranged as a tensor data. In [36], a High Order Singular Value Decomposition (HOSVD) [39] was applied to the AAM [40] coefficients of the training faces to obtain a generative model. In this model, AAM coefficients of training images were factorized into identity and expression subspaces.…”

Section: Related Workmentioning

confidence: 99%

Facial expression transfer method based on frequency analysis

Wei

Tian

Maybank

et al. 2016

Pattern Recognition

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Abstract. We propose a novel expression transfer method based on an analysis of the frequency of multi-expression facial images. We locate the facial features automatically and describe the shape deformations between a neutral expression and non-neutral expressions. The subtle expression changes are important visual clues to distinguish different expressions. These changes are more salient in the frequency domain than in the image domain. We extract the subtle local expression deformations for the source subject, coded in the wavelet decomposition. This information about expressions is transferred to a target subject. The resulting synthesized image preserves both the facial appearance of the target subject and the expression details of the source subject.This method is extended to dynamic expression transfer to allow a more precise interpretation of facial expressions.Experiments on Japanese Female Facial Expression (JAFFE), the extended Cohn-Kanade (CK+) and PIE facial expression databases show the superiority of our method over the state-of-the-art method.

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“…Expressivity is also conveyed by face expressions. Vasilescu and Terzopoulos [28] proposed a multi-linear analysis of tensor faces based on a tensor extension of the conventional matrix Singular Value Decomposition (SVD). Mancini et al [19] map acoustic cues and emotion to expressivity parameters they use to control the expressive virtual head of the Greta ECA.…”

Section: Expressivitymentioning

confidence: 99%

Virtually Cloning Real Human with Motion Style

Rajagopal

Horain

Pélachaud

2012

Advances in Intelligent Systems and Computing

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Abstract. Our goal is to capture style from real human motion so it can be rendered with a virtual agent that represents this human user. We used expressivity parameters to describe motion style. As a first contribution, we propose an approach to estimate a subset of expressivity parameters defined in the literature (namely spatial extent and temporal extent) from captured motion trajectories. Second, we capture the expressivity of real users and then output it to the Greta engine that animates a virtual agent representing the user. We experimentally demonstrate that expressivity can be another clue for identifiable virtual clones of real humans.

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Multilinear Analysis of Image Ensembles: TensorFaces

Cited by 606 publications

References 11 publications

Extended HALS algorithm for nonnegative Tucker decomposition and its applications for multiway analysis and classification

Extended HALS algorithm for nonnegative Tucker decomposition and its applications for multiway analysis and classification

Facial expression transfer method based on frequency analysis

Virtually Cloning Real Human with Motion Style

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