Class is a 3 year targeted research project funded by the European Union Information Society Technologies unit EU IST Cognition.
Scientific Goals
Class will develop a basic cognitive ability for use in intelligent content analysis: the automatic discovery of content categories and attributes from unstructured content streams. The demonstrators will focus on object recognition and scene analysis in images and video with accompanying text streams. Autonomous learning will make recognition more adaptive and allow more general classes and much larger and more varied data sets to be handled.
Technically, the work will combine latent structure models and semi-supervised learning methods from machine learning with advanced visual descriptors from computer vision and state-of-the-art text analysis techniques. Three levels of abstraction will be studied: new individuals (specific people, objects, scenes, actions); new object classes and attributes; and hierarchical categories and relations between entities.
CLASS Projects at Oxford
- Automatic Naming of Characters in TV Video (WP6)
- 2D Human Pose Estimation in TV Shows (WP6)
- Image classification - Caltech datasets (WP 2)
- Learning Visual Attributes (WP3)
CLASS Software at Oxford
- Face detection pipeline (includes facial feature detection and geometric normalization)
- Upper body detector
- Multiple Kernels for Image Classification