Abstract
AbstractThe growing demand for Unmanned Aerial Vehicles (UAVs) in the field of computer vision applications leads the researcher into UAV video analysis for extracting real-time traffic data. This paper systematically reviews studies that apply vehicle detection and extraction methods of Spatio-temporal traffic parameters from UAVs for efficacious traffic analysis. A synthesis of bibliographic sources clarifies the advantages and limitations of different methods of vehicle detection, Spatio-temporal data extraction, and discovers recent trends in the applications of UAVs in real-time traffic analysis. This paper reviews various studies that analytically handle Spatio-temporal data in traffic flow analysis, and paying special attention to infer the effective application of UAVs to extract microscopic traffic data. Thus, the three main questions for this review are: How to detect vehicles from UAV videos? How is the application of UAV performing to estimate traffic flow parameters in the context of present traffic research? What are recent approaches are available for Spatio-temporal data extraction from UAV video data? This paper concludes that there is a clear need for the development of comprehensive techniques for selecting suitable Spatio-temporal data extraction methods for analyzing non-lane-based heterogeneous traffic conditions. KeywordsVehicle detectionSpatio-temporalExtractionUAV
Published Version
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