A Novel Intelligent Image-Processing Parking Systems

Sree Veera Venkata Sai Saran Naraharisetti, Benjamin Greenfield, Benjamin Placzek, Steven Atilho, Mohamad Nassar, M. Mekni
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Abstract

The scientific community is looking for efficient solutions to improve the quality of life in large cities because of traffic congestion, driving experience, air pollution, and energy consumption. This surge exceeds the capacity of existing transit infrastructure and parking facilities. Intelligent Parking Systems (SPS) that can accommodate short-term parking demand are a must-have for smart city development. SPS are designed to count the number of parked automobiles and identify available parking spaces. In this paper, we present a novel SPS based on real-time computer vision techniques. The proposed system provides features including: vacant parking space recognition, inappropriate parking detection, forecast of available parking spaces, and directed indicators toward various sorts of parking spaces (vacant, occupied, reserved and handicapped). Our system leverages existing video surveillance systems to capture, process image sequences, train computer models to understand and interpret the visual world, and provide guidance and information to the drivers.
一种新型智能图像处理停车系统
由于交通拥堵、驾驶体验、空气污染和能源消耗,科学界正在寻找有效的解决方案来改善大城市的生活质量。这种激增超过了现有交通基础设施和停车设施的容量。能够满足短期停车需求的智能停车系统(SPS)是智慧城市发展的必需品。SPS的设计目的是统计停放的汽车数量,并确定可用的停车位。本文提出了一种基于实时计算机视觉技术的SPS。该系统提供的功能包括:空位识别、不适当停车检测、可用停车位预测以及各种停车位(空置、已占用、预留和残障)的定向指示。我们的系统利用现有的视频监控系统来捕获、处理图像序列,训练计算机模型来理解和解释视觉世界,并为驾驶员提供指导和信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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