U.S. Department of Transportation
Federal Highway Administration
1200 New Jersey Avenue, SE
Washington, DC 20590
202-366-4000
Federal Highway Administration Research and Technology
Coordinating, Developing, and Delivering Highway Transportation Innovations
| Project Information | ||
| Project ID: | FHWA-PROJ-14-0051 | |
| Project Name: | Computer Vision Measurements and Analysis to Support Naturalistic Driving Studies. Developing calibration and metrics for automated data extraction algorithm. | |
| Project Status: | Active | |
| Start Date: | June 28, 2013 | |
| End Date: | May 31, 2016 | |
| Contact Information | ||
| Last Name: | Cobb | |
| First Name: | Lincoln | |
| Telephone: | 202-493-3313 | |
| E-mail: | lincoln.cobb@dot.gov | |
| Office: | Office of Safety Research and Development | |
| Program: | Exploratory Advanced Research | |
| Project detail | ||
| Roadmap/Focus area(s): | Safety Data and Analysis | |
| Project Description: | Develop and apply the means to evaluate the automated video analysis algorithms currently being developed under EAR funding. Generalize those results so that researchers in various domains will have standard metrics and data sets available for their internal and external quality assurance/quality check (QA/QC) regimes. | |
| Goals: |
(1) Develop processes and technology to evaluate the automated video analysis algorithms being developed by research teams funded by the Exploratory Advanced Research (EAR) program.
(2) Create standard procedures and datasets, and performance metrics, which can be made available to the video analytics community.
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| Product Type: | Draft standard, specifications, or guidelines Research report Software Training materials | |
| Test Methodology: | (1) Apply performer team algorithms to Virginia Tech Transportation Institute (VTTI) Head Pose Validation data as the starting point. (2) Work with performer teams to understand the performance of each algorithm. (3) Establish standard procedures, datasets, and metrics for algorithm evaluation from lessons learned. | |
| Expected Benefits: | Providing researchers in a variety of video analytics fields with standard approaches to measuring the effectiveness of automated feature extraction algorithms, and automated identity masking algorithms. | |
| Deliverables: | Name: Standard procedures, including standard datasets, for evaluating the performance of automated feature extraction, or automated identity masking algorithms. Product Type(s): Research report, Draft standard, specifications, or guidelines, Software, Training materials Description: Support the development of tools that at least partially automate the process of coding large video datasets, such as the second Strategic Highway Research Program (SHRP2) Naturalistic Driving Studies (NDS) dataset (over 1 million hours of video data), or that automate the masking of the identity of NDS subjects visible in one or more video fields of view. In both cases, automated tools will dramatically open the pool of researchers able to apply large video data sets, such as the NDS, but reducing the time and the cost to do feature extraction or identity masking manually. | |
| FHWA Topics: | Safety--Data and Analysis ToolsHighway-Railroad Grade Crossing | |
| TRT Terms: | Human Factors Research Video Data Information Technology Algorithms Safety |
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| FHWA Disciplines: | Safety |
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| Subject Areas: | Data and Information Technology Safety and Human Factors Research |
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