2014 Poster Sessions : Estimating 3D Attributes of Images from Shape Collections

Student Name : Yangyan Li
Advisor : Leo Guibas
Research Areas: Graphics/HCI
Abstract:
Images are easy to acquire, view, publish, share, and not surprisingly are ubiquitous. They, however, lack critical depth information. We consider the problem of "lifting" image of an object to 3D by exploiting a collection of aligned 3D models of similar or related objects. Our key insight is that even when the imaged object is not contained in the shape collection, the network of shapes implicitly characterizes a shape-specific deformation subspace that regularizing the problem and enables robust diffusion of depth information from the shape collection to the input image.

Bio:
Yangyan Li is a postdoctoral scholar at Geometric Computation Group in Computer Science. Before that, Yangyan received his PhD degree from University of the Chinese Academy of Sciences in 2013, and bachelor degree from Sichuan University in 2008. His primary research interests fall in the field of Computer Graphics with an emphasis on point cloud processing.