We investigate the problem of automatically creating 3D models of man-made environments that we represent as collections of textured planes. A typical approach is to automatically...
Detecting different categories of objects in image and video content is one of the fundamental tasks in computer vision research. The success of many applications such as visual s...
The segmentation and analysis of blood vessels has received much attention in the research community. The results aid numerous applications for diagnosis and treatment of vascular...
This work exploits several machine-learning techniques to address the problem of image-quality prediction of synthetic aperture sonar (SAS) imagery. The objective is to predict th...
Spectral clustering is one of the most widely used techniques for extracting the underlying global structure of a data set. Compressed sensing and matrix completion have emerged a...