We address the problem of learning view-invariant 3D models of human motion from motion capture data, in order to recognize human actions from a monocular video sequence with arbi...
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...
Given a set of 3D model features and their 2D image, model based object recognition determines the correspondences between those features and hence computes the pose of the object...
Active Appearance Models (AAMs) have been popularly used to represent the appearance and shape variations of human faces. Fitting an AAM to images recovers the face pose as well a...
This paper presents an approach for modeling landmark sites such as the Statue of Liberty based on large-scale contaminated image collections gathered from the Internet. Our system...
Xiaowei Li, Changchang Wu, Christopher Zach, Svetl...