Prof. Corso moved to the Electrical Engineering and Computer Science department at the University of Michigan in the 8/2014. He continues his work and research group in high-level computer vision at the intersection of perception, semantics/language, and robotics. Unless you are looking for something specific, historically, here, you probably would rather go to his new page.
Jason J. Corso
Research Pages
Snippets by Topic
* Active Clustering
* Activity Recognition
* Medical Imaging
* Metric Learning
* Semantic Segmentation
* Video Segmentation
* Video Understanding
Selected Project Pages
* Action Bank
* LIBSVX: Supervoxel Library and Evaluation
* Brain Tumor Segmentation
* CAREER: Generalized Image Understanding
* Summer of Code 2010: The Visual Noun
* ACE: Active Clustering
* ISTARE: Intelligent Spatiotemporal Activity Reasoning Engine
* GBS: Guidance by Semantics
* Semantic Video Summarization
Data Sets
* YouCook
* Chen
* UB/College Park Building Facades
Other Information
* Code/Data Downloads
* List of Grants
Real-Time Volume Visualization of Unstructured Grids
Collaborators: Joshua Leven, Jonathan Cohen, Subodh Kumar

We developed a method for the voxelization of large scalar fields with the goal of interactive volume rendering. An adaptive octree is used to optimally sample the underlying unstructured grid. The unstructured grid is embedded into a voxel-space and those regions not corresponding to input data are flagged as being outside of the embedded model. The octree nodes share borders enabling smooth data continuity between them. Gradients are computed and stored with the textures for lighting computation. We integrated this system as a preprocess for an interactive volume system that we developed. This approach leverages the current 3D texture mapping PC hardware for the problem of unstructured grid rendering. We specialize the 3D texture octree to the task of rendering unstructured grids through a novel pad and stencil algorithm, which distinguishes between data and non-data voxels. Both the voxelization and rendering processes efficiently manage large, out-ofcore datasets. The system manages cache usage in main memory and texture memory, as well as bandwidths among disk, main memory, and texture memory. It also manages rendering load to achieve interactivity at all times. It maximizes a quality metric for a desired level of interactivity. It has been applied to a number of large data and produces high quality images at interactive, user-selectable frame rates using standard PC hardware.

Here is an mpg movie describing our work.

[1] J. J. Corso and J. D. Cohen. Out-Of-Core Voxelization of Large Scalar Fields for Interactive Multiresolution Volume Rendering. Technical report, The Johns Hopkins University, 2002. Graphics Lab Technical Report. [ bib ]
[2] J. Leven, J. J. Corso, J. D. Cohen, and S. Kumar. Interactive Visualization of Unstructured Grids Using Hierarchical 3D Textures. In Proceedings of IEEE/SIGGRAPH Symposium on Volume Visualization and Graphics 2002, pages 37-44, 2002. [ bib | .pdf ]

last updated: Tue Jul 29 10:11:57 2014; copyright jcorso