Abstract. In this paper we introduce a new salient object segmentation method, which is based on combining a saliency measure with a conditional random field (CRF) model. The propo...
Esa Rahtu, Juho Kannala, Mikko Salo, Janne Heikkil...
Abstract. We propose a new generative model, and a new image similarity kernel based on a linked hierarchy of probabilistic segmentations. The model is used to efficiently segment ...
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Sparse representation of signals has been the focus of much research in the recent years. A vast majority of existing algorithms deal with vectors, and higher
Ravishankar Sivalingam, Daniel Boley, Vassilios Mo...
Tracking multiple objects is important in many application domains. We propose a novel algorithm for multi-object tracking that is capable of working under very challenging conditi...
This paper introduces a new procedure to handle color in single image super resolution (SR). Most existing SR techniques focus primarily on enforcing image priors or synthesizing i...
Shuaicheng Liu, Michael S. Brown, Seon Joo Kim, Yu...
We introduce a novel nonrigid 2D image registration method that establishes dense and accurate correspondences across images without the need of any manual intervention. Our key in...
Abstract. With the rapid development of fast data acquisition techniques, 3D scans that record the geometric and photometric information of deformable objects are routinely acquire...
Abstract. This paper addresses the problem of registering a 3D model, represented as a cloud of points lying over a surface, to a set of 2D deforming image trajectories in the imag...