Research Projects
Dynamic Category Learning
*** THIS PROJECT IS NO LONGER ACTIVE ***
Trevor Darrell and Tom Yeh1
Dynamic visual category learning calls for efficient adaptation as new training images become available or new categories are defined, existing training images or categories become modified or obsolete, or when categories are divided into subcategories or merged together. We develop novel methods for efficient incremental learning of SVM-based visual category classifiers to handle such dynamic tasks. Our method exploits previous classifier estimates to more efficiently learn the optimal parameters for the current set of training images and categories.
- [1]
- Tom Yeh and Trevor Darrell, Dynamic Visual Category Learning, CVPR 2008
1MIT