Vladimir Kim: 2014 Networks of Shapes, Images, and Programs: The Power of Joint Data Analysis Workshop


Wednesday, April 16, 2014
Location: Fisher Conference Center, Arrillaga Alumni Center

"Affordances: Human-Centric Shape Analysis"
10:30am - 11:00am


As 3D acquisition devices and modeling tools become widely available there is a growing need for automatic algorithms that analyze the semantics and functionality of digitized shapes. Most recent research has focused on analyzing geometric structures of shapes. Our work is motivated by the observation that a majority of man-made shapes are designed to be used by people. Thus, in order to fully understand their semantics, one needs to answer a fundamental question: "how do people interact with these objects?'' As an initial step towards this goal, we offer a novel algorithm for automatically predicting a static pose that a person would need to adopt in order to use an object. Specifically, given an input 3D shape, the goal of our analysis is to predict a corresponding human pose, including contact points and kinematic parameters. This is especially challenging for man-made objects that commonly exhibit a lot of variance in their geometric structure. We address this challenge by observing that contact points usually share consistent local geometric features related to the anthropometric properties of corresponding parts and that human body is subject to kinematic constraints and priors. Accordingly, our method effectively combines local region classification and global kinematically-constrained search to successfully predict poses for various objects. We demonstrate the utility of our method by investigating applications to several challenging problems in computer graphics and computer vision, such as object retrieval and shape matching.


Dr. Vladimir Kim is a postdoctoral scholar at Stanford University. Vladimir joined Stanford after receiving his PhD in the Computer Science Department at Princeton University in 2013. His research interests include geometry processing and analysis of collections of shapes with applications in object recognition, organizing and exploring large geometric repositories, and 3D modeling. He received his B.A. degree in Mathematics and Computer Science from Simon Fraser University in 2008. Vladimir is a recipient of the Siebel Scholarship and the NSERC Postgraduate Scholarship. He was on the International Program Committee for Symposium on Geometry Processing 2013 and 2014, and Eurographics 2014 (short papers).