Content-adaptive traffic prioritization of spatio-temporal scalable video for robust communications over QoS-provisioned 802.11e networks

Fiandrotti, Attilio; Gallucci, Dario; Masala, Enrico; Martin, Juan Carlos De

doi:10.1016/j.image.2010.04.006

Cited by 6 publications

(4 citation statements)

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“…Lam et al [11] created a cooperative framework that uses semantic filtering to select frames, which can achieve better image quality monitoring results over limited bandwidth. Fiandrotti et al [12] proposed a content-adaptive traffic prioritization strategy for H.264/SVC communications over IEEE 802.11e wireless networks. This strategy estimated the perceptual impact of data losses in the different types of enhancement layers for a large set of videos first and proposed a content-adaptive traffic prioritization strategy based on the identification of the most important parts of the enhancement layers of the video sequence by means of a low complexity macroblock analysis process.…”

Section: Related Workmentioning

confidence: 99%

“…High-level quality control methods adopt content dynamics and picture complexity to help the coding of bitrate, which has less computational demanding than VBR scheme. Dynamics of moving objects is a kind of high-level metrics that can greatly improve the high-level quality control with low-level metrics, including the motion detection used in [12].…”

Section: Related Workmentioning

confidence: 99%

“…Traditional bitrate control methods are designed with the only goal to fit the network throughput constraint by CBR or VBR, but not with the goal to give constant and reliable video quality for intelligent applications [11,12]. Considering the video quality degradation with respect to the dynamics of picture complexity, moving objects and wireless networks, constant quality control becomes a more challenging goal.…”

Section: Introductionmentioning

confidence: 99%

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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%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Object-Based Approach for Adaptive Source Coding of Surveillance Video

2019

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“…The presented approaches support network-aware adaptation but neglect content properties. Content-adaptive traffic prioritization schemes were designed by Fiandrotti et al [4]. They leverage a scalable video stream and prioritize different layers of a video according the detected motion.…”

Section: Background and Related Workmentioning

confidence: 99%

Vas

Wilk

Stohr

Effelsberg

2015

Proceedings of the 25th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video

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Even though cellular networks offer a ubiquitous access to the Internet for mobile devices, their throughput is often insufficient for the rising demand for mobile video. Classical video streaming approaches can not cope with bandwidth fluctuations common in those networks. As a result adaptive approaches for video streaming have been proposed and are increasingly adopted on mobile devices. However, existing adaptive video systems often rely on available network resources alone. As video content properties have a large influence on the perception of occurring quality adaptations our belief is that this is not sufficient. In this work, we thus present a support service for a content-aware video adaptation on mobile devices. Based on the actual video content the adaptation process is improved for both the available network resources and the perception of the user. By leveraging the content properties of a video stream, the system is able to keep a stable video quality and at the same time reduce the network load.

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Priority and delay aware packet management framework for real-time video transport over 802.11e WLANs

Wang

Liu

2012

Multimed Tools Appl

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Content-adaptive traffic prioritization of spatio-temporal scalable video for robust communications over QoS-provisioned 802.11e networks

Cited by 6 publications

References 13 publications

Object-Based Approach for Adaptive Source Coding of Surveillance Video

Object-Based Approach for Adaptive Source Coding of Surveillance Video

Vas

Priority and delay aware packet management framework for real-time video transport over 802.11e WLANs

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