This paper adopts the premise that the ‘semantic gap' is an incompletely surveyed feature in the landscape of visual image retrieval, and proposes a framework within which t...
Objects can exhibit different dynamics at different scales, and this is often exploited by visual tracking algorithms. A local dynamic model is typically used to extract image fea...
Leonid Taycher, John W. Fisher III, Trevor Darrell
To bridge the semantic gap in content-based image retrieval, detecting meaningful visual entities (e.g. faces, sky, foliage, buildings etc) in image content and classifying images...
The state of the art in visual object retrieval from large databases is achieved by systems that are inspired by text retrieval. A key component of these approaches is that local ...
James Philbin, Ondrej Chum, Michael Isard, Josef S...
This paper presents a new approach for building semantic image indexing and retrieval systems. Our approach is composed of four phases : (1) knowledge acquisition, (2) weakly-super...