In this paper we propose a representation framework for dynamic multi-sensory knowledge and user context, and its application in media retrieval. We provide a definition of context...
Abstract. Interactively learning from a small sample of unlabeled examples is an enormously challenging task. Relevance feedback and more recently active learning are two standard ...
Charlie K. Dagli, ShyamSundar Rajaram, Thomas S. H...
Aspect-based relevance learning is a relevance feedback scheme based on a natural model of relevance in terms of image aspects. In this paper we propose a number of active learning...
Abstract. This paper investigates the applicability of Informedia shot-based interface features for video retrieval in the hands of novice users, noted in past work as being too re...
This paper deals with the problem of estimating the effort required to maintain a static pose by human beings. The problem is important in developing effective pose classification ...
In this paper, we investigate human visual perception and establish a body of ground truth data elicited from human visual studies. We aim to build on the formative work of Ren, E...
Victoria J. Hodge, Garry Hollier, John P. Eakins, ...
Abstract. This paper presents novel dissimilarity space specially designed for interactive multimedia retrieval. By providing queries made of positive and negative examples, the go...
We introduce an interface for efficient video search that exploits the human ability to quickly scan visual content, after automatic retrieval has arrange the images in expected or...
Alexander G. Hauptmann, Wei-Hao Lin, Rong Yan, Jun...
Abstract. Video databases require that clips are represented in a compact and discriminative way, in order to perform efficient matching and retrieval of documents of interest. We ...