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Quality Analysis on Mobile Devices for Real-Time Feedback

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Book cover MultiMedia Modeling (MMM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9516))

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Abstract

Media capture of live events such as concerts can be improved by including user generated content, adding more perspectives and possibly covering scenes outside the scope of professional coverage. In this paper we propose methods for visual quality analysis on mobile devices, in order to provide direct feedback to the contributing user about the quality of the captured content. Thus, wasting bandwidth and battery for uploading/streaming low-quality content can be avoided. We focus on real-time quality analysis that complements information that can be obtained from other sensors (e.g., stability). The proposed methods include real-time capable algorithms for sharpness, noise and over-/ underexposure which are integrated in a capture app for Android. Objective evaluation results show that our algorithms are competitive to state-of-the art quality algorithms while enabling real-time quality feedback on mobile devices.

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Notes

  1. 1.

    http://opencv.org/.

  2. 2.

    https://github.com/google/grafika.

  3. 3.

    http://www.prestoprime.org.

  4. 4.

    http://www.20203dmedia.eu/.

References

  1. Bosco, A., Bruna, A., Messina, G., Spampinato, G.: Fast method for noise level estimation and integrated noise reduction. IEEE Trans. Consum. Electron. 51(3), 1028–1033 (2005)

    Article  Google Scholar 

  2. Fassold, H., Wechtitsch, S., Hofmann, A., Bailer, W., Schallauer, P., Borgotallo, R., Messina, A., Liu, M., Ndjiki-Nya, P., Altendorf, P.: Automated visual quality analysis for media production. In: IEEE International Symposium on Multimedia (2012)

    Google Scholar 

  3. Feichtenhofer, C., Fassold, H., Schallauer, P.: A perceptual image sharpness metric based on local edge gradient analysis. IEEE Sig. Proc. Letters 20(4), 379–382 (2013)

    Article  Google Scholar 

  4. Ferzli, R., Karam, L.J.: A no-reference objective image sharpness metric based on the notion of just noticeable blur (JNB). IEEE Trans. Image Process. 18(4), 717–728 (2009)

    Article  MathSciNet  Google Scholar 

  5. Hassen, R., Wang, Z., Salama, M.: No-reference image sharpness assessment based on local phase coherence measurement. In: IEEE ICASSP (2010)

    Google Scholar 

  6. Hou, L., Ji, H., Shen, Z.: Recovering over-/underexposed regions in photographs. SIAM J. Imaging Sci. 6(4), 2213–2235 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  7. Ko, J., Kim, C.: Low cost blur image detection and estimation for mobile devices. In: 11th ICACT, vol. 3 (2009)

    Google Scholar 

  8. Schallauer, P., Mörzinger, R.: Film grain synthesis and its application to re-graining. In: SPIE Electronic Imaging (2006)

    Google Scholar 

  9. Sheikh, H., Wang, Z., Cormack, L., Bovik, A.: LIVE image quality assessment database, release 2 [Online]. http://live.ece.utexas.edu/research/quality

  10. Vlachos, T.: Flicker correction for archived film sequences using a nonlinear model. IEEE Trans. Circuits Syst. Video Tech. 14(4), 508–516 (2004)

    Article  Google Scholar 

  11. Yoon, Y.-J., Byun, K.-Y., Lee, D.-H., Jung, S.-W., Ko, S.-J.: A new human perception-based over-exposure detection method for color images. Sensors 14(9), 17159–17173 (2014)

    Article  Google Scholar 

  12. Yousefi, S., Rabiee, H.R., Mianjy, P.: Optimal exposure detection function for digital and smart-phone camera applications. In: IEEE ICCE (2012)

    Google Scholar 

  13. Zlokolica, V., Pizurica, A., Philips, W.: Noise estimation for video processing based on spatio-temporal gradients. IEEE Sig. Proc. Lett. 13(6), 337–340 (2006)

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank their project partners bitmovin for providing the video streaming implementation and VRT for the graphics design. The research leading to these results has received funding from the European Union’s Seventh Framework Programme (FP7/2007-2013) under grant agreement n\(^\circ \) 610370, ICoSOLE (“Immersive Coverage of Spatially Outspread Live Events”, http://www.icosole.eu).

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Correspondence to Werner Bailer .

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Wechtitsch, S., Fassold, H., Thaler, M., Kozłowski, K., Bailer, W. (2016). Quality Analysis on Mobile Devices for Real-Time Feedback. In: Tian, Q., Sebe, N., Qi, GJ., Huet, B., Hong, R., Liu, X. (eds) MultiMedia Modeling. MMM 2016. Lecture Notes in Computer Science(), vol 9516. Springer, Cham. https://doi.org/10.1007/978-3-319-27671-7_30

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  • DOI: https://doi.org/10.1007/978-3-319-27671-7_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27670-0

  • Online ISBN: 978-3-319-27671-7

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