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                Exploratory Advanced Research (EAR) Program Compendium of Papers from Funded Research Projects
FHWA-HRT-23-021_1.pdf (2.2 MB)
      
  Publication Information
                  Publication Type:Other
                  Publication Number:FHWA-HRT-23-021
              Abstract:Researchers for this study developed improved video processing algorithms that can identify more complex behavior and actions of individuals (i.e., pedestrians, drivers, bicyclists) in various traffic situations. The research team wanted to build on existing video-processing algorithms that can identify basic behavior, “primitives” (such as when a subject’s hand is near their head), but cannot always identify a “high-level” behavior (such as talking on a cellphone). Specifically, the researchers aimed to:



Use a bottom-up machine-learning approach to train an algorithm to recognize high-level behaviors using object detection, human-pose estimation, and behavior classification.
	Use a top-down approach to catalog primitive and high-level behaviors and develop a statistical prediction model to link them.



Recommended citation: Federal Highway Administration, Exploratory Advanced Research (EAR) Program Compendium of Papers from Funded Research Projects (Washington, DC: 2023) https://doi.org/10.21949/1521965.
              Publishing Date:January 30, 2023
              Posting Date:01/09/2023
                              Digital Object Identifier:https://doi.org/10.21949/1521965
              Author(s):Kreutzer,
    
          Analiese
              Publishing Office:Human Factors Team
                  FHWA Program(s):Human Factors
              AMRP Program(s):Exploratory Advanced Research
              FHWA Activities:Human Factors
              Pedestrian / Bicycle
              Subject Area:Pedestrians and Bicyclists U.S. DEPARTMENT OF TRANSPORTATION

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