Probabilistic Visual Learning for Object Representation
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Summary
An unsupervised technique for visual learning is presented, which is based on density estimation in high-dimensional spaces using an eigenspace decomposition and is applied to the probabilistic visual modeling, detection, recognition, and coding of human faces and nonrigid objects.
- Type
- article
- Published
- 1997-07-01
- Cited by
- 1,702
- References
- 42
- OpenAlex
- https://openalex.org/W2128716185
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:483975
Keywords
Artificial intelligence, Pattern recognition (psychology), Computer science, Density estimation, Mixture model
References
- Information Theory: 1948-1998 - Guest Editorial
- Automatic systems for the identification and inspection of humans : 28-29 July 1994, San Diego, California
- Face recognition using view-based and modular eigenspaces
- Mixture densities, maximum likelihood, and the EM algorithm
- Shape Discrimination Using Fourier Descriptors
- General learning algorithm for robot vision
- Human Face Recognition and the Face Image Set's Topology
- A Bayesian similarity measure for direct image matching
- Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
- Robust estimation of correlation with applications to computer vision
- Change Detection and Tracking Using Pyramid Transform Techniques
- View-based and modular eigenspaces for face recognition
- Fourier descriptors and neural networks far shape classification
- Modal Matching for Correspondence and Recognition
- Automating the hunt for volcanoes on Venus
- Detection of interest points using symmetry
- Face Recognition: Features Versus Templates
- Automatic location of visual features by a system of multilayered perceptrons
- Human Face Detection in Visual Scenes
- Space-time gestures
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- Image processing in echography and MRI
- A Hybrid Template-Based Composite Classification System
- Modelisation statistique de formes en imagerie cerebrale
- Probabilistic PCA Self-Organizing Maps
- Improving Face Localisation using Claimed Identity for Face Verification
- Transformation-Invariant Clustering and Dimensionality Reduction Using EM
- Subspace methods for face recognition
- Subspace Learning Based on Tensor Analysis
- Adaptive active vision
- Probabilistic methods for motion tracking and generation
- Omnidirectional Video Capturing, Multiple People Tracking and Identification for Meeting Monitoring
- Main character detection in news and movie content
- Bayesian Decision Fusion for Dynamic Multi-Cue Object Detection
- Principal component analysis of gender, ethnicity, age and identity of face images
- Face recognition based on multi-scale singular value features
- Hierarchical Neural Networks for Image Interpretation
- Combating Occlusion and Scene Changes for Camera Position Determination
- Variational Message Passing and its Applications
- Discriminative learning with application to interactive facial image retrieval
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