This paper proposes a novel approach to recognize object categories in point clouds. By quantizing 3D SURF local descriptors, computed on partial 3D shapes extracted from the poin...
A popular approach to pixel labeling problems, such as multiclass image segmentation, is to construct a pairwise conditional Markov random field (CRF) over image pixels where the...
We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...
Matching patches between two images, also known as computing nearest-neighbor fields, has been proven a useful technique in various computer vision/graphics algorithms. But this ...
One challenge when tracking objects is to adapt the object representation depending on the scene context to account for changes in illumination, coloring, scaling, etc. Here, we p...
Ali Borji, Simone Frintrop, Dicky N. Sihite, Laure...
—In this paper we propose a probabilistic model to parameterize human interactive behaviour from human motion. To Support the model taxonomy, we use Laban Movement Analysis (LMA)...
Label fusion strategies are used in multi-atlas image segmentation approaches to compute a consensus segmentation of an image, given a set of candidate segmentations produced by r...
Paul A. Yushkevich, Hongzhi Wang, John Pluta, Bria...
A plenoptic camera captures the 4D radiance about a scene. Recent practical solutions mount a microlens array on top of a commodity SLR to directly acquire these rays. However, th...
Zhan Yu, Jingyi Yu, Andrew Lumsdaine, Todor Georgi...
The choice of the over-complete dictionary that sparsely represents data is of prime importance for sparse codingbased image super-resolution. Sparse coding is a typical unsupervi...
Supervoxel segmentation has strong potential to be incorporated into early video analysis as superpixel segmentation has in image analysis. However, there are many plausible super...