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...
We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
We present a new paradigm for tracking objects in video in the presence of other similar objects. This branch-andtrack paradigm is also useful in the absence of motion, for the di...
Background: Many genome projects are left unfinished due to complex, repeated regions. Finishing is the most time consuming step in sequencing and current finishing tools are not ...
Erik Arner, Martti T. Tammi, Anh-Nhi Tran, Ellen K...
The visualization of complex 3D images remains a challenge, a fact that is magnified by the difficulty to classify or segment volume data. In this paper, we introduce size-based tr...