Computer Vision Group Wins 6 SBIR Proposals

May 4, 2009

In the fall, the Computer Vision Group was awarded 5 Phase I SBIRs and 1 Phase II SBIR, all from DARPA’s Information Processing Techniques Office. The awards were primarily in the area of wide area video analysis and robotic vision.

Detecting and Tracking Multiple Moving Objects from a Moving Platform involves detecting and tracking moving people, vehicles and other objects near a moving robot, from cameras mounted on the robot. The University of Maryland is a subcontractor on this award. On Activity Models for Robots we plan to develop algorithms to recognize the group activity taking place around a robot, based on the observed tracks, and to determine how the robot should participate in the activity. The University of Maryland, the University of California, Berkeley and Georgia Tech will be serving subcontractors on this award. These two efforts will proceed in parallel; however, the tracking effort will provide input to the recognition effort. Both Phase I’s will conclude in late summer, by which time we hope to have preliminary results for the Phase II proposals.

Dismount Tracking in Urban Scenes focuses on detection and tracking in low-resolution wide area video. Rensselaer Polytechnic Institute is serving as the subcontractor on this award. High Resolution 3D Reconstruction from Wide-Area Video focuses on 3D scene reconstruction at a higher spatial resolution than the original video. Brown University is serving as the subcontractor on this award. In addition, Kitware was awarded Phase II funding for Wide-Area Video Storage Techniques. During Phase II, Kitware will be developing video compression technology for an imaging sensor that produces 1.8 Gigapixels at 10 Hz. Brown University and BAE Systems are subcontractors on this Phase II effort.

Functional Interpretation of Activities and Objects is closely related to another award Kitware received last fall, Building Labels in Urban Environments. Through this new Phase I Kitware will continue to develop technology to classify objects based on observed activity. While BLUE is focused on fixed structures such as buildings, the new award has the goal of classifying moving objects based on their behavior. Our partner on this award is Georgia Tech.

Kitware’s Computer Vision group has extensive expertise developing robust solutions for real-world video and image analysis problems. If you are interested in finding out more about Kitware’s state of the art computer vision solutions please contact us at

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