Ongoing Projects
 
 

 Haptics-based surgical simulation supporting cuts


Description: Our work proposes to show that a modular extensible approach that supports cuts in the finite element (more specifically eXtended Finite Element Methods - XFEM) context. We intend to show that such a framework helps in improved speeds and realistic interaction of tissues in surgical simulation.


Researcher: Kishalay Kundu


 Leveraging Graphics Hardware to Accelerate Dynamic Programming


Description: We present a new framework for solving dynamic programming problems on widely available parallel graphics processing hardware. Our method performs dynamic programming at three distinct levels of parallelism, each mapped to a specific layer of hardware and optimized for the memory structure of each layer. We perform linear-space processing at the highest level of the dynamic programming, a quadratic-space algorithm at the middle layer, and a different linear space algorithm on the final layer. The combination of all three running on a single CPU and Graphics Processing Unit (GPU) is a fast, flexible, scalable solution to dynamic programming problems belonging to the Gaussian Elimination Paradigm.


Researchers: John Kloetzli, Brian Strege, Jonathan Decker


 Exaggerated shading for volumetric data


Description: We investigate the use of an illustrative lighting model to accentuate detail in volumetric data. We compare the use of different gradient computation techniques for shading. The technique takes into account multiple scales and is therefore able to accentuate details at various levels.


Researcher: Alark Joshi