A Novel 3D Video Format Identification Algorithm

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 246)


More and more 3D videos are uploaded on the web. It becomes very difficult to find an expected 3D video from online videos because search engineering identifies 2D and 3D format according to the text description of each video currently. In this paper, a novel 3D video format identification algorithm CM is proposed. The frame extraction and L&R image matching are analyzed. CM combines the gray histogram matching (GHM) and the SIFT feature matching (SFM). It can obtain high identification accuracy up to 99.5 % at the price of low computational time. Compared to GHM and SFM, it shows better comprehensive performance.


3D video Automatically format identification Search engineering 


  1. 1.
    Lowe DG (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60(2):91–110CrossRefGoogle Scholar
  2. 2.
    Yanjun, Wang Hongmei Zhang Ke Li (2004) Research progress on image matching. Comput Eng Appl 19:012Google Scholar
  3. 3.
    Zhang T, Wang Z, Zhai J et al (2011) Automatic 3D video format detection. In: IS&T/SPIE electronic imaging. International Society for Optics and Photonics, pp 78631H–78631HGoogle Scholar
  4. 4.
    Zheng G, Jiang X (2012) Introduction of delivery system for frame compatible stereoscopic 3DTV. Video Eng 36(18):36–40Google Scholar
  5. 5.
    Zitova B, Flusser J (2003) Image registration methods: a survey. Image Vis Comput 21(11):977–1000CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.School of Computer Science and EngineeringUniversity of Electronic Science and Technology of ChinaSichuanChina

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