We present an efficient pixel-sampling technique for histogram-based search. Given a template image as a query, a typical histogram-based algorithm aims to find the location of ...
Image feature points are the basis for numerous computer vision tasks, such as pose estimation or object detection. State of the art algorithms detect features that are invariant t...
Bernhard Zeisl, Pierre Fite Georgel, Florian Schwe...
A recent dominating trend in tracking called tracking-by-detection uses on-line classifiers in order to redetect objects over succeeding frames. Although these methods usually deli...
Bernhard Zeisl, Christian Leistner, Amir Saffari, ...
In this paper we propose a multilinear model of human pose and body shape which is estimated from a database of registered 3D body scans in different poses. The model is generated...
Nils Hasler, Hanno Ackermann, Bodo Rosenhahn, Thor...
The integral image is typically used for fast integrating a function over a rectangular region in an image. We propose a method that extends the integral image to do fast integrat...
Many object surfaces are composed of layers of different physical substances, known as layered surfaces. These surfaces, such as patinas, water colors, and wall paintings, have mo...
Tetsuro Morimoto, Robby Tan, Rei Kawakami, Katsush...
We propose a multi-view stereo reconstruction algorithm which recovers urban scenes as a combination of meshes and geometric primitives. It provides a compact model while preservi...
Multiple instance (MI) learning is a recent learning paradigm that is more flexible than standard supervised learning algorithms in the handling of label ambiguity. It has been u...
We address the task of learning a semantic segmentation from weakly supervised data. Our aim is to devise a system that predicts an object label for each pixel by making use of on...