首页|University of Leipzig Researchers Update Understanding of Machine Learning (Mach ine Learning Based Mobile Capacity Estimation for Roadside Parking)
University of Leipzig Researchers Update Understanding of Machine Learning (Mach ine Learning Based Mobile Capacity Estimation for Roadside Parking)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on ar tificial intelligence. According to news reporting out of Leipzig, Germany, by N ewsRx editors, research stated, "The growing number of cars and limited street s pace present significant challenges for cities, applying not only to moving but extending to stationary traffic. The quest for parking spaces exacerbates traffi c congestion, noise, and air pollution, particularly in residential areas." Our news correspondents obtained a quote from the research from University of Le ipzig: "To develop effective parking solutions for these challenges, a trustful data foundation on available parking space capacities, its usage and parking typ e is crucial. Gathering this data is currently time-consuming, requiring manual labeling and street inspections. Moreover, it must be repeated to keep the data current. Research on parking space management has heavily focused on monitoring designated parking lots with fixed cameras to identify free or occupied parking spaces. However, due to privacy concerns fixed cameras are not applicable for th e larger part of the street space in European cities. This paper introduces a no vel computer visionbased method for automatically collecting parking space capa cities and parking type information. Our approach combines both street view and aerial imagery, which are recorded by a moving camera source. We tackle challeng es in geo-referencing images, identifying parking types, classifying moving and stationary cars and dealing with partial occlusions in images. By not permanentl y recording the same environment, our approach lowers the surveillance risk, mak ing parking capacity estimation scalable."
University of LeipzigLeipzigGermanyEuropeCyborgsEmerging TechnologiesMachine Learning
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