A real-time vehicle flow-measuring algorithm for complex urban intersection in the daytime

Transit agencies are increasingly using video cameras to fight crime and terrorism. As the volume of video data increases, the existing digital video surveillance systems provide the infrastructure only to capture, store and distribute video, while leaving the task of threat detection exclusively to human operators. The objective of this research project was to study and develop an evaluation framework for commercial video analytics systems. A state-of-the-art research literature survey was conducted. Identified strengths, weaknesses, future directions of research and state-of-the-art commercial video analytics products were surveyed. Product capabilities were identified by working together with vendors and analyzing the available literature offered by the providers. Use of analytic technology in transit agencies in Florida was analyzed. A technology survey among the largest agencies in the state indicates very low use of video analytics, significant skepticism, and poor general knowledge of the technology and its capabilities. Based on existing general evaluation frameworks, an evaluation framework for video analytics technology was developed, including annotation guidelines, scoring metrics, and implementation of the scoring metrics in the scoring software.

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A real-time vehicle flow-measuring algorithm for complex urban intersection in the daytime

Cited by 3 publications

References 3 publications

Understanding Transit Scenes: A Survey on Human Behavior-Recognition Algorithms

Understanding Transit Scenes: A Survey on Human Behavior-Recognition Algorithms

Video Driven Traffic Modelling in Paramics

Evaluation of Smart Video for Transit Event Detection

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