Project: Surveillance Systems for Interpreting Scenes

Understanding Human or Machine Interactions

This research has two main threads, one applied to civil engineering, and one applied to socialization of older adults in common spaces.

Civil Engineering

This research seeks reliably and automatically track work progress and multiple resources using video in order to reproduce the daily workflow activities associated to a construction worksite. The goal is to remove the manual nature of construction site activities and progress measurement of processes that involve workers, large machines, and materials. Demonstrating that an active vision system can effectively analyze and assess work-site progress will assist project managers by reducing the time spent monitoring and interpreting project status and performance, thus enabling increased attention to control of cost and schedule. The track data will be interpreted and used to provide understanding of the spatio-temporal evolution of a worksite for automatically generating knowledge about worksite operations. In an information-based framework, much effort is spent acquiring and interpreting information. In a knowledge-based framework, efforts are allocated to making decisions based on the interpreted information.

The image processing and tracking flow diagram below roughly depicts the procedure. In addition to the video stream, the system does require some additional information of site knowledge to be provided. This site knowledge is used to decode the scene activities and make the proper inferences. Usually it consists of site layout information that would be available as part of the site layout plan.

Older Adults and Socialization

In collaboration with the D-Matters Labs in the School of Industrial Design, we have been focusing on quantifying the social interactions that occur in the common areas of retirement communities. Our preliminary efforts have been devoted to designing a surveillance system that can automatically generate the necessary quantitative data in a format consistent with that of professional manual annotation software (such as Observer XT). In particular, Dr. Rebola's D-Matters lab seeks to design technological interventions that will promote socialization amongst older adults. Having the automated system would assist with verifying the impact of the technological interventions.

Students: Gbolabo Ogunmakin.

Collaborators: Andre Bormann, RAPIDS Lab / Jochen Teizer, D-Matters / Claudia Rebola.


This research was supported in part by the National Science Foundation (#0846750, #1030472). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.