Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota
Intelligent transportation systems depend on being able to track vehicle operations and collect accurate traffic data.
This project targets a hardware-based video detection system for real-time vehicle detection. To allow real-time
detection, customized hardware implementation of the system is targeted instead on the traditional computer-based
implementation of the system. The system includes four main processing steps. First, a camera is used to capture
images. Second, the captured images are segmented using the Mixture-of-Gaussian algorithm. Without sacrificing
the segmentation accuracy, researchers modified the Mixture-of-Gaussian algorithm to allow more efficient and
economical hardware implementation in terms of design overhead and hardware resources. Third, the
segmentation regions are extracted and validated as the objects of interests. In the last step, the validation result
will be wirelessly transmitted to a variable message sign, which displays necessary traffic information. Since the
system design includes integration of diverse devices, the video design kit from Xilinx is used. Such a hardware-based
vehicle detection system has been experimented tested with practical videos of traffic scene.
Intelligent Transportation Systems Institute,
Center for Transportation Studies,
University of Minnesota
Tang, Hua; Peng, Li.
Development of a New Tracking System Based on CMOS Vision Processor Hardware, Phase II Prototype Demonstration.
Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota.
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