True-Error Detection of Compressed Video: Temporal Exploration

  • Xudong Zhao
  • Shenghong Li
  • Chenglin Zhao
  • Shilin Wang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 246)


In this paper, we propose a novel error detection method in the temporal domain for H.264/AVC encoded video streams. The corrupted macro blocks (MBs) are detected by exploiting the correlations between MBs in the neighboring two frames. Correlation coefficient and mean of residual block are introduced to quantify the correlations in the temporal domain. A supervised classifier based on probability density functions of proposed features is designed for error detection and expectation maximum algorithm is employed to find the optimal parameters of the classifier. Eight corrupted H.264/AVC encoded video sequences are used in our experimental work for test, and experimental results show that the proposed error detection method can detect the corrupted MBs effectively.


H.264/AVC Error detection Expectation maximum algorithm 



This work is funded by National Science Foundation of China (61271316, 61071152), 973 Program (2010CB731403, 2010CB731406, 2013CB329605) of China, Chinese National “Twelfth Five-Year” Plan for Science & Technology Support (2012BAH38 B04), Key Laboratory for Shanghai Integrated Information Security Management Technology Research, and Chinese National Engineering Laboratory for Information Content Analysis Technology.


  1. 1.
    Gao Y, Wang J, Chen X, Zhang D, Yang X, Wang J (2006) Object geometry based error resilient video coding. In: IEEE International Conference on Image Processing, Atlanta, GA, 8–11 October, 2006, pp. 789–792Google Scholar
  2. 2.
    Superiori L, Nemethova O, Rupp M (2006) Performance of a H.264/AVC error detection algorithm based on syntax analysis. In: International Conference on Advances in Mobile Computing and Multimedia, 4–6 December, 2006, Yogyakarta, Indonesia, pp. 1–10Google Scholar
  3. 3.
    Superiori L, Nemethova O, Rupp M (2007) Detection of visual impairments in the pixel domain of corrupted h.264/avc packets. In: IEEE International Picture Coding Symposium, Lisbon, Portugal, November, 2007, pp. 7–9Google Scholar
  4. 4.
    Ye S, Lin X, Sun Q (2003) Content based error detection and concealment for image transmission over wireless channel. In: IEEE International Symposium on Circuits and Systems, Thailand, May 2003, vol. 2, pp. 368–371Google Scholar
  5. 5.
    Farrugia RA, Debono CJ (2007) Enhancing error resilience in wireless transmitted compressed video sequences through a probabilistic neural network core. In: IEEE International Picture Coding Symposium, Lisbon, Portugal, November, 2007Google Scholar
  6. 6.
    Farrugia RA, Debono CJ (2008) A robust error detection mechanism for h.264/avc coded video sequences based on support vector machines. IEEE Trans Circ Syst Video Techn 18:1766–70CrossRefGoogle Scholar
  7. 7.
    Dempster A, Laird N, Rubin D (1977) Maximum likelihood from incomplete data via the em algorithm. J Roy Stat Soc 99:1–38MathSciNetGoogle Scholar
  8. 8.
    Ver. 18.2, J.S.: H.264/avc software coordination. In:

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Xudong Zhao
    • 1
  • Shenghong Li
    • 1
  • Chenglin Zhao
    • 2
  • Shilin Wang
    • 1
  1. 1.Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghaiChina
  2. 2.School of Information and Communication EngineeringBeijing University of Posts and TelecommunicationsBeijingChina

Personalised recommendations