Vision Based Motion Tracking for Risk Assesment During Seismic Events

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Project Name Vision-Based Motion Tracking For Risk Assesment During Seismic Events
Team Members Tara C. Hutchinson, Falko Kuester, Sherman Auduong and Kai-Uwe Doerr
Project Sponsor Consortium of Universities for Research in Earthquake Engineering (CUREE) and Kajima Corporation (CUREE-Kajima Joint Venture, Phase V)
SI Calibration SI user interface SI camera array



Previous experiences during earthquake events emphasize the need for new technologies for real-time monitoring and assessment of facilities with high value nonstructural elements such as equipment or other contents. Moreover, there is substantial limitation in our ability to rapidly evaluate and identify potential hazard zones within a structure, exposing rescue workers, society and the environment to unnecessary risks. A real-time monitoring system, integrated with critical warning systems, would allow for improved channeling of resources. In recognition of these issues, we are investigating vision-based systems, specifically digital red-light (filtered) cameras and full wavelength (unfiltered) video cameras, and developing a methodology for using these advanced monitoring techniques for risk assessment during earthquake events. Our approach focuses on developing a non-intrusive, high-resolution, high-speed network of these two types of vision-based systems and corresponding detection, tracking and analysis algorithms for monitoring equipment and contents in buildings. We are using the full-scale shake table experiments funded by PEER to evaluate the robustness and accuracy of the different systems. These experiments utilize conventional (wired) transducers, providing a unique dataset for evaluating and refining the vision-based approach. Funding for this project is provided a joint program between the Consortium of Universities for Research in Earthquake Engineering (CUREE) and Kajima Corporation (CUREE-Kajima phase V).



  • Hutchinson, T. C., Chaudhuri, R. S., Kuester, F., and Auduong, S. (2005). Light-based motion tracking of equipment subjected to earthquake motions. Journal of Computing in Civil Engineering, ASCE, 19(3):292–303.

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