Latent variable models and factors analysis
Latent variable models and factors analysis
GTM: the generative topographic mapping
Neural Computation
Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
Prediction with Gaussian processes: from linear regression to linear prediction and beyond
Learning in graphical models
Proceedings of the 1998 conference on Advances in neural information processing systems II
Probabilistic visualisation of high-dimensional binary data
Proceedings of the 1998 conference on Advances in neural information processing systems II
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A family of algorithms for approximate bayesian inference
A family of algorithms for approximate bayesian inference
Style-based inverse kinematics
ACM SIGGRAPH 2004 Papers
Local distance preservation in the GP-LVM through back constraints
ICML '06 Proceedings of the 23rd international conference on Machine learning
Hierarchical Gaussian process latent variable models
Proceedings of the 24th international conference on Machine learning
Multifactor Gaussian process models for style-content separation
Proceedings of the 24th international conference on Machine learning
Blind separation of nonlinear mixtures by variational Bayesian learning
Digital Signal Processing
Topologically-constrained latent variable models
Proceedings of the 25th international conference on Machine learning
Gaussian processes for canonical correlation analysis
Neurocomputing
Synthesising Novel Movements through Latent Space Modulation of Scalable Control Policies
SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
Ambiguity Modeling in Latent Spaces
MLMI '08 Proceedings of the 5th international workshop on Machine Learning for Multimodal Interaction
Monocular 3D tracking of articulated human motion in silhouette and pose manifolds
Journal on Image and Video Processing - Anthropocentric Video Analysis: Tools and Applications
Learning Generative Models for Multi-Activity Body Pose Estimation
International Journal of Computer Vision
Sparse Kernel Learning and the Relevance Units Machine
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Autonomous Robots
Non-linear matrix factorization with Gaussian processes
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Efficient computation of PCA with SVD in SQL
Proceedings of the 2nd Workshop on Data Mining using Matrices and Tensors
Heteroscedastic Probabilistic Linear Discriminant Analysis with Semi-supervised Extension
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
WiFi-SLAM using Gaussian process latent variable models
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Exploiting motion correlations in 3-D articulated human motion tracking
IEEE Transactions on Image Processing
Multi-relational learning with Gaussian processes
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Generating Video Textures by PPCA and Gaussian Process Dynamical Model
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Regularized Kernel Local Linear Embedding on Dimensionality Reduction for Non-vectorial Data
AI '09 Proceedings of the 22nd Australasian Joint Conference on Advances in Artificial Intelligence
Speech-Driven Facial Animation Using a Shared Gaussian Process Latent Variable Model
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Twin Gaussian Processes for Structured Prediction
International Journal of Computer Vision
Probabilistic amplitude demodulation
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Stable spaces for real-time clothing
ACM SIGGRAPH 2010 papers
Gaussian process latent variable models for human pose estimation
MLMI'07 Proceedings of the 4th international conference on Machine learning for multimodal interaction
Fundamenta Informaticae - Intelligent Data Analysis in Granular Computing
Tracking human pose with multiple activity models
Pattern Recognition
A manifold representation as common basis for action production and recognition
KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
Relevance units latent variable model and nonlinear dimensionality reduction
IEEE Transactions on Neural Networks
International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction
Learning GP-BayesFilters via Gaussian process latent variable models
Autonomous Robots
Gaussian mixture modeling with Gaussian process latent variable models
Proceedings of the 32nd DAGM conference on Pattern recognition
Multifactor feature extraction for human movement recognition
Computer Vision and Image Understanding
Transfer latent variable model based on divergence analysis
Pattern Recognition
Facial movement based recognition
MIRAGE'11 Proceedings of the 5th international conference on Computer vision/computer graphics collaboration techniques
KI'11 Proceedings of the 34th Annual German conference on Advances in artificial intelligence
A probabilistic framework for learning kinematic models of articulated objects
Journal of Artificial Intelligence Research
ECML'06 Proceedings of the 17th European conference on Machine Learning
Target tracking without line of sight using range from radio
Autonomous Robots
Gaussian process motion graph models for smooth transitions among multiple actions
Computer Vision and Image Understanding
Two methods for sparsifying probabilistic canonical correlation analysis
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
Evolutionary kernel density regression
Expert Systems with Applications: An International Journal
Continuous character control with low-dimensional embeddings
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Dimensionality reduction via compressive sensing
Pattern Recognition Letters
On evolutionary approaches to unsupervised nearest neighbor regression
EvoApplications'12 Proceedings of the 2012t European conference on Applications of Evolutionary Computation
Memory-restricted latent semantic analysis to accumulate term-document co-occurrence events
Pattern Recognition Letters
Proceedings of the ACM Symposium on Applied Perception
Coupled Action Recognition and Pose Estimation from Multiple Views
International Journal of Computer Vision
Neural Processing Letters
The Journal of Machine Learning Research
A unifying probabilistic perspective for spectral dimensionality reduction: insights and new models
The Journal of Machine Learning Research
A particle swarm embedding algorithm for nonlinear dimensionality reduction
ANTS'12 Proceedings of the 8th international conference on Swarm Intelligence
A unified energy minimization framework for model fitting in depth
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume 2
Unsupervised nearest neighbors with kernels
KI'12 Proceedings of the 35th Annual German conference on Advances in Artificial Intelligence
Learning morphological maps of galaxies with unsupervised regression
Expert Systems with Applications: An International Journal
Information capacity of full-body movements
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Simultaneous monocular 2d segmentation, 3d pose recovery and 3d reconstruction
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Simultaneous particle tracking in multi-action motion models with synthesized paths
Image and Vision Computing
Probabilistic movement modeling for intention inference in human-robot interaction
International Journal of Robotics Research
Nonparametric guidance of autoencoder representations using label information
The Journal of Machine Learning Research
Reconstructing whole-body motions with wrist trajectories
Graphical Models
Partial-update dimensionality reduction for accumulating co-occurrence events
Pattern Recognition Letters
Joint view-identity manifold for infrared target tracking and recognition
Computer Vision and Image Understanding
Charting-based subspace learning for video-based human action classification
Machine Vision and Applications
Regressing Local to Global Shape Properties for Online Segmentation and Tracking
International Journal of Computer Vision
Efficient tracking using a robust motion estimation technique
Multimedia Tools and Applications
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Summarising a high dimensional data set with a low dimensional embedding is a standard approach for exploring its structure. In this paper we provide an overview of some existing techniques for discovering such embeddings. We then introduce a novel probabilistic interpretation of principal component analysis (PCA) that we term dual probabilistic PCA (DPPCA). The DPPCA model has the additional advantage that the linear mappings from the embedded space can easily be non-linearised through Gaussian processes. We refer to this model as a Gaussian process latent variable model (GP-LVM). Through analysis of the GP-LVM objective function, we relate the model to popular spectral techniques such as kernel PCA and multidimensional scaling. We then review a practical algorithm for GP-LVMs in the context of large data sets and develop it to also handle discrete valued data and missing attributes. We demonstrate the model on a range of real-world and artificially generated data sets.