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Multimedia Systems Development (MSD) course project

An Efficient Video Similarity Search Algorithm

This project uses efficient video retrieval technique in a large storage. There are two challenging problems in detecting video similarity from a large storage similarity measurement and search method. This project uses a novel video feature computation of image characteristic code based on spatial-temporal distribution of video frame sequences.

The video similarity is measured based on the calculation of the number of similar video components. This system is on the basis of four types of tables: The first is video CIT (VCIT) containing the number of video components. The second is database CIT (DCIT) recording video ID and the number of video
component of each video. The third is search table (ST) including the corresponding database CIT of each video clip.The forth is video similarity table (VST) recording similar video ID and video similarity measure. In order to improve the query throughput and fast accessing, it uses Cluster indexing mechanism in database.
[1] An Efficient Video Similarity Search Algorithm. Zheng Cao, Ming Zhu. IEEE Transactions
on Consumer Electronics, Vol. 56, No. 2, May 2010.

Name: Chittampally Vasanth Raja
RollNo: 10IT05F

Download as Pdf :Abstract_10IT05F

  1. June 3, 2013 at 1:41 am

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  1. February 28, 2011 at 2:41 pm
  2. May 5, 2011 at 2:09 pm

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