In this paper we develop a systematic theory about local structure of moving images in terms of Galilean differential invariants. We argue that Galilean invariants are useful for s...
We present an approach to visual object-class recognition and segmentation based on a pipeline that combines multiple, holistic figure-ground hypotheses generated in a bottom-up,...
This paper presents a framework for using high-level visual information to enhance the performance of automatic color constancy algorithms. The approach is based on recognizing spe...
Esa Rahtu, Jarno Nikkanen, Juho Kannala, Leena Lep...
State of the art methods for image and object re-
trieval exploit both appearance (via visual words) and
local geometry (spatial extent, relative pose). In large
scale problems,...
Michal Perdoch (Czech Technical University), Ondre...
We propose use of an appearance manifold with embedded covariance matrix as a technique for recognizing 3D objects from images that are influenced by geometric and quality-degrade...