— We consider learning in a transductive setting using instance-based learning (k-NN) and present a method for constructing a data-dependent distance “metric” using both labe...
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
In this paper we propose a novel non-rigid volume registration based on discrete labeling and linear programming. The proposed framework reformulates registration as a minimal path...
Ben Glocker, Nikos Komodakis, Nikos Paragios, Geor...
Abstract— This paper studies routing schemes and their distributed construction in limited wireless networks, such as sensor or mesh networks. We argue that the connectivity of s...
We present a novel ``dynamic learning'' approach for an intelligent image database system to automatically improve object segmentation and labeling without user interven...