Extended VQM model for predicting 3D video quality considering ambient illumination context

Nur, G.; Arachchi, Hemantha Kodikara; Dogan, S.; Kondoz, A.M.

doi:10.1109/3dtv.2011.5877180

Cited by 9 publications

(5 citation statements)

References 6 publications

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“…This method is based on the detection of edge and color degradations. Nur et al [2011] extended the standardized VQM model using the ambient illumination, and content related features such as motion, structural feature, and luminance contrast to estimate the 3D video quality. Jin et al [2011] presented a quality assessment method for stereoscopic video based on 3D-DCT transform.…”

Section: Quality Assessment In Multiview 3d Videomentioning

confidence: 99%

A new methodology to derive objective quality assessment metrics for scalable multiview 3D video coding

Roodaki

Hashemi

Shirmohammadi

2012

ACM Trans. Multimedia Comput. Commun. Appl.

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With the growing demand for 3D video, efforts are underway to incorporate it in the next generation of broadcast and streaming applications and standards. 3D video is currently available in games, entertainment, education, security, and surveillance applications. A typical scenario for multiview 3D consists of several 3D video sequences captured simultaneously from the same scene with the help of multiple cameras from different positions and through different angles. Multiview video coding provides a compact representation of these multiple views by exploiting the large amount of inter-view statistical dependencies. One of the major challenges in this field is how to transmit the large amount of data of a multiview sequence over error prone channels to heterogeneous mobile devices with different bandwidth, resolution, and processing/battery power, while maintaining a high visual quality. Scalable Multiview 3D Video Coding (SMVC) is one of the methods to address this challenge; however, the evaluation of the overall visual quality of the resulting scaled-down video requires a new objective perceptual quality measure specifically designed for scalable multiview 3D video. Although several subjective and objective quality assessment methods have been proposed for multiview 3D sequences, no comparable attempt has been made for quality assessment of scalable multiview 3D video. In this article, we propose a new methodology to build suitable objective quality assessment metrics for different scalable modalities in multiview 3D video. Our proposed methodology considers the importance of each layer and its content as a quality of experience factor in the overall quality. Furthermore, in addition to the quality of each layer, the concept of disparity between layers (inter-layer disparity) and disparity between the units of each layer (intra-layer disparity) is considered as an effective feature to evaluate overall perceived quality more accurately. Simulation results indicate that by using this methodology, more efficient objective quality assessment metrics can be introduced for each multiview 3D video scalable modalities. ACM Reference Format:Roodaki, H., Hashemi, M. R., and Shirmohammadi, S. 2012 A new methodology to derive objective quality assessment metrics for scalable multiview 3D video coding. ACM Trans. Multimedia Comput.

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Section: Quality Assessment In Multiview 3d Videomentioning

confidence: 99%

A new methodology to derive objective quality assessment metrics for scalable multiview 3D video coding

Roodaki

Hashemi

Shirmohammadi

2012

ACM Trans. Multimedia Comput. Commun. Appl.

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“…Consequently, 725 videos were generated at 25 f ps rate. This data set has been already used in [11,14,18]. Subjective tests are based on SAMVIQ [19], and user scores are based on continuous scale in the range of [0 (worst)-100 (best)] for overall 3D stereoscopic video quality.…”

Section: Nr-rr Content and Quality Feature Extractionmentioning

confidence: 99%

“…On the other hand, there is a lack of exclusive objective quality metrics for 3D videos. Several 3D quality metrics can be found in [8][9][10][11]. These 3D quality metrics are dependent on availability of reference video.…”

Section: Introductionmentioning

confidence: 99%

Automatic subjective quality estimation of 3D stereoscopic videos: NR-RR approach

Malekmohamadi

2017

2017 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video (3dtv-Con)

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A method for estimating subjective quality score of 3D stereoscopic video is proposed which is based on decision trees. The output of this estimation can be fed into encoding and transmission units for compensation. The proposed method operates with minimum dependency on reference video. Content characteristics, no reference (NR) and reduced reference (RR) quality metrics are extracted and summarised prior to training stage. Content features are based on spatio-temporal activities within depth layers. Quality features include NR blockiness, NR blurriness and RR 3D stereoscopic video quality metric. Due to fast and accurate requirements for the quality estimation, decision trees are employed where a 0.94 accuracy is achieved.

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“…In [3] and [4], the authors introduce metrics that are based on the luminance components of image pixels and compare the results with subjective evaluations, minimizing the difference between the metric values and the responses of test subjects. In [5], the authors also build their metric on the basis of subjective tests.…”

Section: Related Workmentioning

confidence: 99%

Towards automatic stereo-video quality assessment and detection of color and sharpness mismatch

Voronov

Vatolin

Sumin

et al. 2012

2012 International Conference on 3D Imaging (IC3D)

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In this paper, we address the problem of stereo-video quality assessment. We introduce objective no-reference metrics for automatic color-and sharpness-mismatch detection in video captured using stereo cameras. The algorithms are based on view matching and reconstruction. A fast block-based color-independent algorithm for stereo matching is proposed. We verify the applicability of the proposed metrics by assessing the quality of full-length films. This quality-assessment procedure reveals scenes distorted during film production or postproduction and enables film comparison in terms of stereoscopic quality.Index Termsstereoscopic video, stereo video, 3D video, color mismatch, sharpness mismatch, focus mismatch, video quality

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Extended VQM model for predicting 3D video quality considering ambient illumination context

Cited by 9 publications

References 6 publications

A new methodology to derive objective quality assessment metrics for scalable multiview 3D video coding

A new methodology to derive objective quality assessment metrics for scalable multiview 3D video coding

Automatic subjective quality estimation of 3D stereoscopic videos: NR-RR approach

Towards automatic stereo-video quality assessment and detection of color and sharpness mismatch

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