No-Reference Objective Video Quality Measure for Frame Freezing Degradation

Dumic, Emil; Bjelopera, Anamaria

doi:10.3390/s19214655

Cited by 1 publication

(1 citation statement)

References 25 publications

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“…The statistical models of the freeze characteristics may be included in wireless VR simulators supporting the development of physical layer, medium access layer, and higher layer functionalities. They also may serve as network-disturbance models for VR QoE studies, e.g., generating realistic freeze events in wireless VR stimuli to support the development of perceptual quality measures, similar as is done for conventional videos [21,22].…”

Section: Motivation and Contributionsmentioning

confidence: 99%

Video Freeze Assessment of TPCAST Wireless Virtual Reality: An Experimental Study

et al. 2022

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Wireless virtual reality (VR) offers a seamless user experience but has to cope with higher sensitivity to temporal impairments induced on the wireless link. Apart from bandwidth dynamics and latency, video freezes and their lengths are important temporal performance indicators that impact on the quality of experience (QoE) of networked VR applications and services. This paper reports an experimental study that focuses on the VR video frame freeze length characteristics of a wireless VR solution. A comprehensive measurement campaign using a commercial TPCAST wireless VR solution with an HTC Vive head-mounted display was conducted to obtain real VR video traces. The number of detected freezes and freeze intensities are reported both accumulated over four room quadrants as well as for each of the four quadrants subject to six transmitter-receiver distances. The statistical analysis of the VR video traces of the different experiments includes histograms of the freeze lengths and cumulative complementary histograms of the freeze length. The results of this analysis offer insights into the density of the underlying distributions of the measured data, illustrate the impact of the room topology on the freeze characteristics, and suggest the statistical modeling of the freeze characteristics as exponential and geometric distributions. The statistical models of the freeze characteristics may be included in wireless VR simulators supporting the development of physical layer, medium access layer, and higher layer functionalities. They also may serve as network-disturbance models for VR QoE studies, e.g., generating realistic freeze events in wireless VR stimuli.

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Section: Motivation and Contributionsmentioning

confidence: 99%