A Fast and Performance-Maintained Transcoding Method Based on Background Modeling for Surveillance Video

Geng, Man; Zhang, Xianguo; Liang, Luhong; Huang, Tiejun

doi:10.1109/icme.2012.65

Cited by 10 publications

(4 citation statements)

References 9 publications

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“…ROI methods can enhance image quality in target parts of a video while the remaining parts are transmitted at low quality. A previous study [23] used dynamic background modeling to divide MBs into foreground and background regions and proposed strategies to increase the transcoding speed of surveillance video. Another study [24] used a superpixel-based MB selection method to obtain accurate shape information when detecting motion objects using a low bit ROI coding system.…”

Section: Related Workmentioning

confidence: 99%

Object-Based Approach for Adaptive Source Coding of Surveillance Video

2019

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Intelligent analysis of surveillance videos over networks requires high recognition accuracy by analyzing good-quality videos that however introduce significant bandwidth requirement. Degraded video quality because of high object dynamics under wireless video transmission induces more critical issues to the success of smart video surveillance. In this paper, an object-based source coding method is proposed to preserve constant quality of video streaming over wireless networks. The inverse relationship between video quality and object dynamics (i.e., decreasing video quality due to the occurrence of large and fast-moving objects) is characterized statistically as a linear model. A regression algorithm that uses robust M-estimator statistics is proposed to construct the linear model with respect to different bitrates. The linear model is applied to predict the bitrate increment required to enhance video quality. A simulated wireless environment is set up to verify the proposed method under different wireless situations. Experiments with real surveillance videos of a variety of object dynamics are conducted to evaluate the performance of the method. Experimental results demonstrate significant improvement of streaming videos relative to both visual and quantitative aspects.

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Section: Related Workmentioning

confidence: 99%

Object-Based Approach for Adaptive Source Coding of Surveillance Video

2019

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“…A number of studies have highlighted the improved performance and efficiency of the DBM based McFIS scheme [5] [6] [19]- [21]. DBM is also applied in recent studies in the area of transcoding technique for video surveillance [22].…”

Section: Introductionmentioning

confidence: 99%

Adaptive weighted non-parametric background model for efficient video coding

et al. 2017

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“…Studies show the improved performance and computational efficiency of the McFIS-based video coding schemes [8][12][19] [20] [23]. DBM is also applied in recent studies in the area of transcoding technique for video surveillance [24].…”

Section: Introductionmentioning

confidence: 99%

An efficient video coding technique using a novel non-parametric background model

Chakraborty

Paul

Murshed

et al. 2014

2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)

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Video coding technique with a background frame, extracted from mixture of Gaussian (MoG) based background modeling, provides better rate distortion performance by exploiting coding efficiency in uncovered background areas compared to the latest video coding standard. However, it suffers from high computation time, low coding efficiency for dynamic videos, and prior knowledge requirement of video content. In this paper, we present a novel adaptive weighted non-parametric (WNP) background modeling technique and successfully embed it into HEVC video coding standard. Being non-parametric (NP), the proposed technique naturally exhibits superior performance in dynamic background scenarios compared to MoG-based technique without a priori knowledge of video data distribution. In addition, the WNP technique significantly reduces noise-related drawbacks of existing NP techniques to provide better quality video coding with much lower computation time as demonstrated through extensive comparative studies against NP, MoG and HEVC techniques. Index Terms-Video coding, Background model, Nonparametric model, Coding efficiency, Coding performance The author has requested enhancement of the downloaded file. All in-text references underlined in blue are linked to publications on ResearchGate. The author has requested enhancement of the downloaded file. All in-text references underlined in blue are linked to publications on ResearchGate.

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A Fast and Performance-Maintained Transcoding Method Based on Background Modeling for Surveillance Video

Cited by 10 publications

References 9 publications

Object-Based Approach for Adaptive Source Coding of Surveillance Video

Object-Based Approach for Adaptive Source Coding of Surveillance Video

Adaptive weighted non-parametric background model for efficient video coding

An efficient video coding technique using a novel non-parametric background model

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