We present a technique for local image representation that is invariant to viewpoint for scenes with arbitrary non-planar shape. We show that generic viewpoint invariance can be a...
We propose an algorithm to perform causal inference of the state of a dynamical model when the measurements are corrupted by outliers. While the optimal (maximumlikelihood) soluti...
Andrea Vedaldi, Hailin Jin, Paolo Favaro, Stefano ...
We advocate the use of Scaled Gaussian Process Latent Variable Models (SGPLVM) to learn prior models of 3D human pose for 3D people tracking. The SGPLVM simultaneously optimizes a...
Raquel Urtasun, David J. Fleet, Aaron Hertzmann, P...
We propose a new method to estimate multiple rigid motions from noisy 3D point correspondences in the presence of outliers. The method does not require prior specification of num...
Automatic detection of a falling person in video is an important problem with applications in security and safety areas including supportive home environments and CCTV surveillance...
We present an approach for inferring the topology of a camera network by measuring statistical dependence between observations in different cameras. Two cameras are considered con...
We describe a technique for reconstructing probable occluded surfaces from 3-D range images. The technique exploits the fact that many objects possess shape symmetries that can be...
This paper presents a novel approach that represents an image or a set of images using a nonorthogonal binary subspace (NBS) spanned by boxlike base vectors. These base vectors po...
Photometric stereo is a fundamental approach in Computer Vision. At its core lies a set of image irradiance equations each taken with a different illumination. The vast majority o...
In this paper, we present a novel segmentationinsensitive approach for mining common patterns from 2 images. We develop an algorithm using the Earth Movers Distance (EMD) framewor...