Images, Frames, and Connectionist Hierarchies
Neural Computation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Speaker Modeling Based on Constrained Nonnegative Tensor Factorization
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
Auditory sparse representation for robust speaker recognition based on tensor structure
EURASIP Journal on Audio, Speech, and Music Processing - Intelligent Audio, Speech, and Music Processing Applications
Efficient illumination independent appearance-based face tracking
Image and Vision Computing
IEICE - Transactions on Information and Systems
Locating nose-tips and estimating head poses in images by tensorposes
IEEE Transactions on Circuits and Systems for Video Technology
Mode-kn factor analysis for image ensembles
IEEE Transactions on Image Processing
Independent components extraction from image matrix
Pattern Recognition Letters
A Dynamical Shape Prior for LV Segmentation from RT3D Echocardiography
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
Evaluation of head pose estimation for studio data
CLEAR'06 Proceedings of the 1st international evaluation conference on Classification of events, activities and relationships
Singular value decompositions and low rank approximations of tensors
IEEE Transactions on Signal Processing
Fast subspace-based tensor data filtering
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Tensor distance based multilinear locality-preserved maximum information embedding
IEEE Transactions on Neural Networks
EURASIP Journal on Advances in Signal Processing - Special issue on advanced image processing for defense and security applications
Journal of Computer Science and Technology
Kernel discriminant transformation for image set-based face recognition
Pattern Recognition
Sparse non-negative tensor factorization using columnwise coordinate descent
Pattern Recognition
CIBB'10 Proceedings of the 7th international conference on Computational intelligence methods for bioinformatics and biostatistics
Classifying faces with discriminant isometric feature mapping
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
MRCS'06 Proceedings of the 2006 international conference on Multimedia Content Representation, Classification and Security
Gaze estimation from low resolution images
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
Plant classification based on multilinear independent component analysis
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Real-time face tracking and recognition by sparse eigentracker with associative mapping to 3D shape
Image and Vision Computing
Color face tensor factorization and slicing for illumination-robust recognition
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Component-based locomotion composition
EUROSCA'12 Proceedings of the 11th ACM SIGGRAPH / Eurographics conference on Computer Animation
Component-based locomotion composition
Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Gait identification based on MPCA reduction of a video recordings data
ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
Optimal calculation of tensor learning approaches
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
Multi-dimensional causal discovery
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Independent Components Analysis (ICA) maximizes the statistical independence of the representational components of a training image ensemble, but it cannot distinguish between the different factors, or modes, inherent to image formation, including scene structure, illumination, and imaging. We introduce a nonlinear, multifactor model that generalizes ICA. Our Multilinear ICA (MICA) model of image ensembles learns the statistically independent components of multiple factors. Whereas ICA employs linear (matrix) algebra, MICA exploits multilinear (tensor) algebra. We furthermore introduce a multilinear projection algorithm which projects an unlabeled test image into the N constituent mode spaces to simultaneously infer its mode labels. In the context of facial image ensembles, where the mode labels are person, viewpoint, illumination, expression, etc., we demonstrate that the statistical regularities learned by MICA capture information that, in conjunction with our multilinear projection algorithm, improves automatic face recognition.