Raindrop-tampered scene detection and traffic flow estimation for nighttime traffic surveillance

NCUIR > College of Electrical Engineering & Computer Science > Department of Computer Science and information Engineering > journal & Dissertation > Item 987654321/107173

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/107173

Title:	Raindrop-tampered scene detection and traffic flow estimation for nighttime traffic surveillance
Authors:	鄭旭詠;Yu, Chih-Chang;Cheng, Hsu-Yung;Jian, Yi-Fan
Contributors:	資訊電機學院資訊工程學系
Keywords:	Cameras;Estimation;Feature extraction;Raindrop-tampered camera;regression;salient regions;Surveillance;traffic flow analysis;Training;Vehicles;Videos
Date:	2015-06-01
Issue Date:	2026-04-23 13:58:47 (UTC+8)
Publisher:	Institute of Electrical and Electronics Engineers Inc.;IEEE
Abstract:	摘要： In this paper, we propose an intelligent highway surveillance system that performs self-diagnosis and detects conditions when the camera is seriously tampered by raindrops at night. The system also provides solutions to analyze the traffic flow under the challenging nighttime raindrop-tampered conditions. To deal with the challenging scenes, we extract effective features via salient region detection and block segmentation. The extracted features are used to train a support vector machine to achieve self-diagnosis. For traffic flow analysis, we use the extracted features in the region of interest and construct a regression model to get an estimated vehicle count for each frame. The vehicle counts in consecutive frames form a vehicle count sequence. We propose a mapping model to acquire the desired per-minute traffic flow from the vehicle count sequence. The model utilizes state transfer likelihoods and takes into account the length of the segmented vehicle count sequence. The experiments on highly challenging data sets have demonstrated that the proposed system can effectively estimate the traffic flow for raindrop-tampered highway surveillance cameras at night. 其他題名： TITS 出版者： IEEE 出版日期： 2015-06-01 出處： IEEE transactions on intelligent transportation systems, 2015-06, Vol.16 (3), p.1518-1527 資源來源： IEEE Electronic Library (IEL) 識別號： ISSN: 1524-9050 識別號： EISSN: 1558-0016 識別號： DOI: 10.1109/TITS.2014.2365033 識別號： CODEN: ITISFG
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

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