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Impact of the Content on Subjective Evaluation of Audiovisual Quality:

Impact of the Content on Subjective Evaluation of Audiovisual Quality: What dimensions influence our perception?. J.Lassalle , L.Gros (Orange Labs ) , G.Coppin (Télécom Bretagne) & T . Morineau (UBS). Current Context.

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Impact of the Content on Subjective Evaluation of Audiovisual Quality:

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  1. Impact of the Content on Subjective Evaluation of Audiovisual Quality: What dimensions influence our perception? J.Lassalle, L.Gros (Orange Labs) , G.Coppin (Télécom Bretagne) & T. Morineau (UBS)

  2. Current Context Audiovisual (AV) perceived quality is the result of the interaction between sound and image qualities: • what are the impacts of A and/or V degradations on the perceived AVQ and consequently on overall QoE ? Several studies have shown a test material dependency on perceived quality: • Consequently, methods for evaluating AV quality should consider the influence of contents (regarding the influence of audio, video and the relationship between audio and video) to avoid uncontrolled effects Today, only the ITU P.911 method is dedicated to AV quality evaluation in a passive viewing context: • It suggests a classification of test sequences but only on the basis of individual characteristics of the content A and V separately • Thus, it does not provide recommendations on the characterization of the AV event (i.e. considering semantic link between audio and video) VQEG june 2012

  3. Experiment 1Expert Characterization Corpus: • Dance • Theatre • Opera • Sport • Documentary Expert characterization: extraction of 9 low-levels descriptors • Gwinner & Lalaurette, 2004 (MPEG7); Amiar, 1995 • 5 Semantic Descriptors: audio-visual relationship/diegesis (sound in, sound off, off-screen sound), sound expression (speech, music, sound effects), number of characters (few, some, many), content dynamic (low, moderate, high) and dominant modality (A, V, AV) • 4 Technical Descriptors: brightness (low, moderate, high), color temperature (hot, moderate, cool), dynamic camera (low, moderate, high), and level of details (low, moderate, high). => The entire corpus has been characterized by considering these descriptors VQEG june 2012

  4. Experiment 1Used Description Material VQEG june 2012

  5. Experiment 1Protocol 28 non expert participants Corpus: • 20 sequences (8-10s), extracted from the 5 contents characterized by the expert Task: • Quality Evaluation (P.911 9-point scale) : • AVQ, VQ and AQ • Evaluation of 4 expert low-level descriptors (unchanging nature for the other criteria) : • dominant modality, color, brightness and content dynamic • Evaluation of the five additional high-level descriptors: • 3 Hedonic descriptors: interest, valence and arousal (Self-Assessment Manikin-Scales) • 2 Semantic descriptors: comprehension and quantity of information VQEG june 2012

  6. Experiment 1Results • Verify the relevance of descriptors • all semantic, technical and hedonic descriptors and Quality scores significantly depend on the sequence and more generally on the content • Obtain a corpus of AV sequences representing these different descriptors VQEG june 2012

  7. Experiment 1Results Impact of “Sequence” condition on MOS for AV, A and V qualities VQEG june 2012

  8. Experiment 2Content and Degradations: which interactions ? 35 non expert Participants Corpus: • 200 sequences: 20 sequences (from experiment 1) * 10 degradation conditions • AV asynchrony (1500 ms audio delay), • A bitrate variation (at 64Kbps/8Khz), • V bitrate variations (between 93 to1600 Kbps), • Freeze of frames packets • A packet loss (10%) • A and V degradation combined Task: • AV quality assessment (as recommended by P.911 – only overall AV quality) • SEOVQ software was used to perform the test and collect the judgments of participants VQEG june 2012

  9. Experiment 2Results • Study the potential impacts of low-level descriptors on the overall perceived AV quality, in interaction with various degradations • discomfort > for “verbal” sequences compared to "nonverbal" sequences (sound / music), for asynchrony degradation Effect of Sound Type VQEG june 2012

  10. Experiment 2Results • Study the potential impacts of low-level descriptors on the overall perceived AV quality, in interaction with various degradations • discomfort > for “verbal” sequences compared to "nonverbal" sequences (sound / music), for asynchrony degradation Effect of Sound Type S14 tagged “speech” and “sound-off” : a Diegesis effect VQEG june 2012

  11. Experiment 2Results • Obtain a catalog of interactions between degradation and some semantic and/or technical descriptors • Effect of dynamic, modality and interest on AVQ scores VQEG june 2012

  12. Experiment 2Results • Obtain a catalog of interactions between degradation and some semantic and/or technical descriptors • Effect of dynamic, modality and interest on AVQ scores VQEG june 2012

  13. Experiment 2Results • Obtain a catalog of interactions between degradation and some semantic and/or technical descriptors • Interactions between dynamic, modality and interest and the factor “Degradation” Illustration of modality and “Degradation“ interaction VQEG june 2012

  14. Conclusions and normalization perspectives It would be relevant to consider: • a complete content characterization which takes dominant modality, dynamic, sound type (with sounds-effects class) and diegesis (sound-in/off/off screen) into account • a multi criteria evaluation in addition to the overall AVQ evaluation with: • a separate assessment of Audio and Video quality (as recommended in P.920) • a specific question on asynchrony to allow participants to express their discomfort on this kind of degradation VQEG june 2012

  15. Thank you for your attention VQEG june 2012

  16. References Test material dependency on perceived quality • D. H. Hands, “A basic multimedia quality model,” IEEE Trans. Multimedia, vol.6(6), pp.806-816, December 2004 • N. F. Dixon, and L. Spitz, “The diction of auditory visual desynchrony,” Perception, vol. 9, pp. 719–721, 1980 • M. P. Hollier, A. N. Rimell, D.S. Hand, and R.M. Voelcker, “Multi-modal perception,” J. BT Technol., vol. 17, pp. 35–46 January 1999 A/V interaction • J. G. Beerends, and F. E. De Caluwe, “The influence of video quality on perceived audio quality and vice versa,” J. Audio Eng. Soc., vol. 47(5), pp. 355-362, May 1999 • ITU-T Contribution COM 12-19-E, Relation between audio, video and audiovisual qualitys, KPN, The Netherlands, December 1997 VQEG june 2012

  17. Current Context Table A.1/P.911 – Video content categories VQEG june 2012

  18. Current Context Table A.2/P.911 – Audio content categories VQEG june 2012

  19. VQEG june 2012

  20. Naive characterization: protocol Experiment 1Protocol VQEG june 2012

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