Abstract
Surveillance videos have the feature of static background, which has been exploited in surveillance video coding by the background reference techniques. However, in long surveillance videos that last for several hours to several days, the appearance of background is varying due to the change of illumination, which incurs inefficiency of the background reference techniques. Moreover, intra frames in video coding cannot make use of the background reference and thus incur bit-rate burst. To solve this problem, we propose to separate illuminance out of appearance, and introduce a new kind of references known as reflectance reference (RefRef). RefRef consists of the reflectance component of the background in surveillance videos. The RefRef is invariant to illumination change, and thus can be put always in memory when encoding/decoding the surveillance videos of a specific camera. Especially, RefRef can be used for intra frames, together with the encoding/decoding of the illuminance component. Since the illuminance is usually more smooth than the appearance, RefRef provides higher compression efficiency for intra frames. Experimental results show that the RefRef method leads to more than 50% BD-rate reduction, compared to the High Efficiency Video Coding (HEVC) anchor, on typical surveillance videos under all-intra configuration.
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References
Bossen, F.: Common test conditions and software reference configurations. JCTVC-H1100, presented at the 8th meeting of Joint Collaborative Team on Video Coding (JCT-VC), San Jose, CA, USA, February 2012
Chen, F., Li, H., Li, L., Liu, D., Wu, F.: Block-composed background reference for high efficiency video coding. IEEE Trans. Circuits Syst. Video Technol. 27(12), 2639–2651 (2017)
Gorur, P., Amrutur, B.: Skip decision and reference frame selection for low-complexity H.264/AVC surveillance video coding. IEEE Trans. Circuits Syst. Video Technol. 24(7), 1156–1169 (2014)
Hauagge, D., Wehrwein, S., Bala, K., Snavely, N.: Photometric ambient occlusion for intrinsic image decomposition. IEEE Trans. Pattern Anal. Mach. Intell. 38(4), 639–651 (2016)
Hong, R., Hu, Z., Wang, R., Wang, M., Tao, D.: Multi-view object retrieval via multi-scale topic models. IEEE Trans. Image Process. 25(12), 5814–5827 (2016)
Hong, R., Zhang, L., Tao, D.: Unified photo enhancement by discovering aesthetic communities from Flickr. IEEE Trans. Image Process. 25(3), 1124–1135 (2016)
Hong, R., Zhang, L., Zhang, C., Zimmermann, R.: Flickr circles: aesthetic tendency discovery by multi-view regularized topic modeling. IEEE Trans. Multimed. 18(8), 1555–1567 (2016)
Li, B., Xu, J., Zhang, D., Li, H.: QP refinement according to Lagrange multiplier for high efficiency video coding. In: IEEE International Symposium on Circuits and Systems (ISCAS), pp. 477–480. IEEE (2013)
Paul, M., Lin, W., Lau, C.T., Lee, B.S.: A long-term reference frame for hierarchical B-picture-based video coding. IEEE Trans. Circuits Syst. Video Technol. 24(10), 1729–1742 (2014)
Richardson, I.E.: H.264 and MPEG-4 Video Compression: Video Coding for Next-Generation Multimedia. Wiley, New York (2004)
Sullivan, G.J., Ohm, J., Han, W.J., Wiegand, T.: Overview of the high efficiency video coding (HEVC) standard. IEEE Trans. Circuits Syst. Video Technol. 22(12), 1649–1668 (2012)
Zhang, X., Tian, Y., Huang, T., Dong, S., Gao, W.: Optimizing the hierarchical prediction and coding in HEVC for surveillance and conference videos with background modeling. IEEE Trans. Image Process. 23(10), 4511–4526 (2014)
Acknowledgment
This work was supported by the National Key Research and Development Plan under Grant 2016YFC0801001, the Natural Science Foundation of China under Grants 61772483, 61390512, and 61331017.
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Liu, D., Zhang, Z., Chen, F., Li, H., Wu, F. (2018). Reflectance Reference for Intra-Frame Coding of Surveillance Video. In: Hong, R., Cheng, WH., Yamasaki, T., Wang, M., Ngo, CW. (eds) Advances in Multimedia Information Processing – PCM 2018. PCM 2018. Lecture Notes in Computer Science(), vol 11164. Springer, Cham. https://doi.org/10.1007/978-3-030-00776-8_44
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DOI: https://doi.org/10.1007/978-3-030-00776-8_44
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