Optimization is a powerful paradigm for expressing and solving problems in a wide range of
areas, and has been successfully applied to many vision problems. Discrete optimization …

Optical flow estimation is one of the oldest and still most active research domains in
computer vision. In 35 years, many methodological concepts have been introduced and …

Medical image segmentation, the task of partitioning an image into meaningful parts, is an
important step toward automating medical image analysis and is at the crux of a variety of …

While social Virtual Reality (VR) applications such as Facebook Spaces are becoming
popular, they are not compatible with classic mobile-or cloud-based solutions due to their …

Among the most exciting advances in early vision has been the development of efficient
energy minimization algorithms for pixel-labeling tasks such as depth or texture …

Powerful statistical models that can be learned efficiently from large amounts of data are
currently revolutionizing computer vision. These models possess a rich internal structure …

People's personal social networks are big and cluttered, and currently there is no good way
to automatically organize them. Social networking sites allow users to manually categorize …

The field of discrete calculus, also known as" discrete exterior calculus", focuses on finding a
proper set of definitions and differential operators that make it possible to operate the …

State-of-the-art research on MRFs, successful MRF applications, and advanced topics for
future study. This volume demonstrates the power of the Markov random field (MRF) in …

We present spectral matting: a new approach to natural image matting that automatically
computes a basis set of fuzzy matting components from the smallest eigenvectors of a …