Guest Editorial: Scenes, Images and Objects
Authors: Frédéric Labrosse · Reyer Zwiggelaar · Yonghuai Liu · Bernie Tiddeman
DOI: 10.1007/s11263-012-0562-3
Abstract:
An important aspect of current computer vision research is the analysis of scenes, and particularly the extraction of their 3D structure and their segmentation into objects. Linked to that is the interpretation of the images and/or recognition of types of images, either from the output of the 3D reconstruction and segmentation or directly from the images. Solving such problems is often accomplished by combining a variety of methods and/or attributes of the images, as the papers in this special issue show.
Ladicky et al. provide us with a framework to unify dense stereo reconstruction and object segmentation, where both are formulated as Random Field labelling which are jointly optimized. Evaluation is done on an enhanced Leuven data set, which is publicly available.
