详情

Exploring AI-based Video Segmentation and Saliency Computation to Optimize Imagery-acquisition from Moving Vehicles

项目名称：	Exploring AI-based Video Segmentation and Saliency Computation to Optimize Imagery-acquisition from Moving Vehicles
摘要：	In this project, the research team proposes to employ machine learning (ML) techniques for creating adaptive sampling profiles and a data-driven, opportunistic approach to data acquisition from moving sensors. The immediate goal is to drastically cut down the cost of deploying video and image sensors, making them more practical. To this end, the team plans to explore a novel research direction: detecting the salient frames in video data captured by sensors using computer vision, video segmentation algorithms. Then, a data-driven approach using ML will be employed to find the control features that enhance sensor data acquisition and prevent huge waste to the memory and storage resources. The team plans to evaluate their proposed methods by demonstrating their effectiveness in a pedestrian mobility analysis. The team provides a method to count pedestrians from a moving car instead of relying on the conventional methods of using fixed sensors or human counters, which due to their high cost, suffer from very limited spatial coverage.
状态：	Active
资金：	88674
资助组织：	Office of the Assistant Secretary for Research and Technology
执行机构：	Connected Cities for Smart Mobility towards Accessible and Resilient Transportation Center (C2SMART)
开始时间：	20210301
预计完成日期：	20220228
主题领域：	Data and Information Technology；Highways；Pedestrians and Bicyclists