We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...
We propose a family of kernels between images, defined as kernels between their respective segmentation graphs. The kernels are based on soft matching of subtree-patterns of the r...
We propose a method for learning using a set of feature representations which retrieve different amounts of information at different costs. The goal is to create a more efficient ...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
Local spatiotemporal features or interest points provide compact but descriptive representations for efficient video analysis and motion recognition. Current local feature extract...
Due to the structural heterogeneity of XML, queries are often interpreted approximately. This is achieved by relaxing the query and ranking the results based on their relevance to ...