Strong lighting is common in natural scenes yet is often viewed as a nuisance for object pose estimation and tracking. In human shape and pose estimation, cast shadows can be conf...
Alexandru O. Balan, Michael J. Black, Horst W. Hau...
In this paper we present a novel boosting algorithm for supervised learning that incorporates invariance to data transformations and has high generalization capabilities. While on...
We consider the task of creating a 3-d model of a large novel environment, given only a small number of images of the scene. This is a difficult problem, because if the images are...
In this paper, we introduce a new image descriptor for broad Image Categorization, the Progressive Randomization (PR), that uses perturbations on the values of the Least Significa...
Online camera recalibration is necessary for long-term deployment of computer vision systems. Existing algorithms assume that the source of recalibration information is a set of f...
Andrew W. Fitzgibbon, Duncan P. Robertson, Antonio...
We present a fast and accurate framework for registration of multi-modal volumetric images based on decoupled estimation of registration parameters utilizing spatial information i...
Parastoo Sadeghi, Ramtin Shams, Richard I. Hartley...
Manual labeling of objects in videos is a tedious task. We present an approach which automatically propagates the labels from a single frame to the next ones. We tackle the challe...
Julien Fauqueur, Gabriel J. Brostow, Roberto Cipol...
We present a practical, stratified autocalibration algorithm with theoretical guarantees of global optimality. Given a projective reconstruction, the first stage of the algorithm ...
This paper presents a fast, accurate, and novel method for the problem of estimating the number of humans and their positions from background differenced images obtained from a si...
Lan Dong, Vasu Parameswaran, Visvanathan Ramesh, I...