Abstract. Variational problems, which are commonly used to solve lowlevel vision tasks, are typically minimized via a local, iterative optimization strategy, e.g. gradient descent....
Werner Trobin, Thomas Pock, Daniel Cremers, Horst ...
Abstract. This paper presents a novel framework for detecting abnormal pedestrian and vehicle behaviour by modelling cross-correlation among different co-occurring objects both loc...
Abstract. This paper proposes a novel curvilinear structure detector, called Optimally Oriented Flux (OOF). OOF finds an optimal axis on which image gradients are projected in orde...
An approach to the analysis of images of regular texture is proposed in which lattice hypotheses are used to define statistical models. These models are then compared in terms of t...
Object detection and pixel-wise scene labeling have both been active research areas in recent years and impressive results have been reported for both tasks separately. The integra...
Different materials reflect light in different ways, so reflectance is a useful surface descriptor. Existing systems for measuring reflectance are cumbersome, however, and although...
Computer vision has traditionally focused on extracting structure, such as depth, from images acquired using thin-lens or pinhole optics. The development of computational imaging i...
In patch-based object recognition, using a compact visual codebook can boost computational efficiency and reduce memory cost. Nevertheless, compared with a large-sized codebook, it...
A large photo collection downloaded from the internet spans a wide range of scenes, cameras, and photographers. In this paper we introduce several novel priors for statistics of su...
Sujit Kuthirummal, Aseem Agarwala, Dan B. Goldman,...
We consider the problem of imaging a scene with a given depth of field at a given exposure level in the shortest amount of time possible. We show that by (1) collecting a sequence ...