Intelligent video surveillance for checking attendance of traffic controllers in level crossing

Ke, Xiang; Wang, Xuanyin; Cao, Songxiao; Fu, Xiaojie

doi:10.1007/s12204-013-1464-4

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…Moreover individual trajectories are associated in series of cameras that are adjacent to each other. The system proposed by X. Ke et al, [8] automatically checks the attendance of traffic controllers based on detection scheme. Detection and tracking scheme includes motion detection technique with feature matching and color segmentation.…”

Section: Related Workmentioning

confidence: 99%

IP Camera Based Video Surveillance Using Object’s Boundary Specification

Chaudhry¹,

Suleman²

2016

IJITCS

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The ability to detect and track object of interest from sequence of frames is a crit ical and vital problem of many vision systems developed as yet. This paper presents a smart surveillance system that tracks objects of interest in a sequence of frames in their own defined respective boundaries. The objects of interest are registered or saved within the system. We have proposed a unique tracking algorith m using co mbination of SURF feature matching, Kalman filtering and temp late matching approach. Moreover, an efficient technique is proposed that is used to refine reg istered object image, ext ract object of interest and remove extraneous image area fro m it. The system will track reg istered objects in their respective boundaries using real time v ideo generated through two IP cameras positioned in front of each other.

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Section: Related Workmentioning

confidence: 99%

IP Camera Based Video Surveillance Using Object’s Boundary Specification

Chaudhry¹,

Suleman²

2016

IJITCS

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“…Traffic safety has always been a topic of significant interest. The low visibility caused by haze and heavy rainfall is an important factor that consistently leads to human travel accidents [1]. When visibility is low, highway managers usually close roads to ensure traffic safety.…”

Section: Introductionmentioning

confidence: 99%

Video visibility prediction method for foggy weather based on spatio-temporal variation features

Li,

Dai,

Yao

et al. 2024

Fourth International Conference on Computer Vision and Data Mining (ICCVDM 2023)

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Visibility prediction affects travel safety and is a major concern for highway and airline authorities. However, current visibility prediction methods based on video data usually capture some features in static images, which are relatively simple and are not commonly used for continuous variation information of video data. This study proposes a visibility prediction method based on the spatio-temporal variation features of a video. Through the spatial division of the images from the video, the optimal spatial distribution of different features in the image is mapped using the correlation matrix, and the spatio-temporal variation information of the video is extracted based on the short-term stationary features of fog spatio-temporal evolution. Finally, the relationship between the spatiotemporal variation features of the video and visibility is constructed by combining the time-frequency localization features of the wavelet transform and the self learning ability of the neural network. Compared with the predicted results of traditional static image features, theR2, RMSE, and MAE of the visibility prediction results were improved by 0.1698 and reduced by 58.4142 and 20.0427, respectively. In addition, the R2, RMSE, and MAE of the prediction results based on wavelet neural networks can reach 0.9817, 28.3365, and 19.2098, respectively, compared to current mainstream prediction methods. This fully proves the scientificity and effectiveness of the method, which can be applied to the accurate monitoring of visibility in fog weather based on video data.

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Intelligent video surveillance for checking attendance of traffic controllers in level crossing

Cited by 2 publications

References 11 publications

IP Camera Based Video Surveillance Using Object’s Boundary Specification

IP Camera Based Video Surveillance Using Object’s Boundary Specification

Video visibility prediction method for foggy weather based on spatio-temporal variation features

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