Kernel methods have been popular over the last decade to solve many computer vision, statistics and machine learning problems. An important, both theoretically and practically, op...
Head pose estimation from images has recently attracted much attention in computer vision due to its diverse applications in face recognition, driver monitoring and human computer...
Dong Huang, Markus Storer, Fernando DelaTorre, Hor...
This paper proposes a novel method that preserves the geometrical structure created by variation of multiple factors in analysis of multiple factor models, i.e., multifactor analy...
The problem of finding one-dimensional structures in images and videos can be formulated as a problem of searching for cycles in graphs. In [11], an untangling-cycle cost functio...
In this paper we present a framework for the recognition of collective human activities. A collective activity is defined or reinforced by the existence of coherent behavior of i...
We characterize a class of videos consisting of very small but potentially complicated motions. We find that in these scenes, linear appearance variations have a direct relations...
Robert Pless, Nathan Jacobs, Michael Dixon, Austin...
We propose a new method to quickly and accurately predict 3D positions of body joints from a single depth image, using no temporal information. We take an object recognition appro...
Jamie Shotton, Andrew Fitzgibbon, Mat Cook, Andrew...
Exact recovery from contaminated visual data plays an important role in various tasks. By assuming the observed data matrix as the addition of a low-rank matrix and a sparse matri...
Yadong Mu, Jian Dong, Xiaotong Yuan, Shuicheng Yan
This paper addresses the problem of simultaneous tracking of multiple targets in a video. We first apply object detectors to every video frame. Pairs of detection responses from ...