Accurate intrinsic camera calibration is essential to any computer vision task that involves image based measurements. Given its crucial role with respect to precision, a large nu...
We present a novel off-line algorithm for target segmentation and tracking in video. In our approach, video data is represented by a multi-label Markov Random Field model, and seg...
We present a novel method to detect curves with unknown endpoints using minimal path techniques. Our work builds on the state of the art minimal path techniques currently used to ...
Linear subspace representations of appearance variation are pervasive in computer vision. In this paper we address the problem of robustly matching them (computing the similarity ...
Given a video and associated text, we propose an automatic annotation scheme in which we employ a latent topic model to generate topic distributions from weighted text and then mo...
Chris Engels, Koen Deschacht, Jan Hendrik Becker, ...
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
Mapping planar structure in vision-based SLAM can increase robustness and significantly improve efficiency of map representation. However, previous systems have implemented planar...
We present a fully automatic approach for facial expression recognition based on a representation of facial motion using a vocabulary of local motion descriptors. Previous studies...
We propose a novel general framework with a boosting algorithm to achieve active object classification by view selection. The proposed framework actively decides the next best vie...