We present a latent hierarchical structural learning method for object detection. An object is represented by a mixture of hierarchical tree models where the nodes represent objec...
Leo Zhu, Yuanhao Chen, Antonio Torralba, Alan Yuil...
We present efficient and accurate algorithms for interference detection among objects undergoing polynomial deformation. The scope of our algorithms include physically-based model...
Merlin Hughes, Christopher DiMattia, Ming C. Lin, ...
We present an efficient multi stage approach to detection of deformable objects in real, cluttered images given a single or few hand drawn examples as models. The method handles de...
In this paper, we present an integrated system for skin deformation that is able to handle deformations due to both the skeleton animation and collisions. This method is based on ...
We propose a new approach to collision and self– collision detection of dynamically deforming objects that consist of tetrahedrons. Tetrahedral meshes are commonly used to repre...
Matthias Teschner, Bruno Heidelberger, Matthias M&...