自动检测长期停放的车辆

Vincenzo Carletti, P. Foggia, Antonio Greco, Alessia Saggese, M. Vento
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引用次数: 11

摘要

在智能交通系统中,路边违规停车的检测越来越受到人们的关注,因为它可能会导致交通拥堵或事故。本文提出了一种对传统监控摄像机采集的视频进行分析并自动检测停在禁区内车辆的方法。介绍了两个主要贡献:首先,与被停车辆相关的时空信息被热图编码;其次,背景不是通过评估车辆在单个时间瞬间的运动来更新的,而是考虑到编入热图的车辆的整个运动。两个广泛采用的数据集,即iLids和PETS 2000,已被用于实验评估所提出的方法,所取得的结果,与最先进的方法进行比较,证实了其有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic detection of long term parked cars
The detection of illegal roadside parking is becoming more and more interesting in the field of intelligent transportation systems, since it may cause traffic congestion or accidents. In this paper we propose a method able to analyze videos acquired by traditional surveillance cameras and to automatically detect the vehicles stopped in a forbidden area. Two main contributions have been introduced: first, spatio temporal information related to the stopped vehicles are encoded by a heat map; second, the background is not updated by evaluating the movement of the vehicle in a single time instant, but instead the whole movement of the vehicles, encoded into the heat map, is taken into account. Two widely adopted datasets, namely the iLids and the PETS 2000, have been used to experimentally evaluate the proposed approach and the results achieved, compared with state of the art methodologies, confirm its effectiveness.
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