United States Department of Transportation
i
Exploring AI-Based Video Segmentation and Saliency Computation To Optimize Imagery-Acquisition From Moving Vehicles
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2023-10-01
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[PDF-2.32 MB]
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Edition:Final report, 3/1/21-10/31/23
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Abstract:In this study, a new dataset and tool were generated describing and mapping street-level infrastructure. The presented dataset, StreetAware, is generated from more than 7 hours of synchronized data collected at urban intersections by specialized Reconfigurable Environmental Intelligence Platform (REIP) sensors developed by the Visualization and Data Analytics (VIDA) Research Center at NYU. To demonstrate these key features of the data, we present four uses for the data that are not possible on many existing datasets. (1) to track objects using the multiple perspectives of multiple cameras from both audio (sound-based localization) and visual modes, (2) to associate audio events with their respective visual representations using audio and video, (3) to track the amount of each type of object in a scene over time, i.e., occupancy, and (4) to measure the speed of a pedestrian while crossing a street using multiple synchronized views and the high-resolution capability of the cameras.
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