Efficient and robust detection of duplicate videos in a large database

  • Sarkar A
  • Singh V
  • Ghosh P
 et al. 
  • 26


    Mendeley users who have this article in their library.
  • 26


    Citations of this article.


We present an efficient and accurate method for duplicate video detection in a large database using video fingerprints. We have empirically chosen the color layout descriptor, a compact and robust frame-based descriptor, to create fingerprints which are further encoded by vector quantization (VQ). We propose a new nonmetric distance measure to find the similarity between the query and a database video fingerprint and experimentally show its superior performance over other distance measures for accurate duplicate detection. Efficient search cannot be performed for high-dimensional data using a nonmetric distance measure with existing indexing techniques. Therefore, we develop novel search algorithms based on precomputed distances and new dataset pruning techniques yielding practical retrieval times. We perform experiments with a database of 38 000 videos, worth 1600 h of content. For individual queries with an average duration of 60 s (about 50% of the average database video length), the duplicate video is retrieved in 0.032 s, on Intel Xeon with CPU 2.33 GHz, with a very high accuracy of 97.5%.

Author-supplied keywords

  • Color layout descriptor (CLD)
  • Duplicate detection
  • Nonmetric distance
  • Vector quantization (VQ)
  • Video fingerprinting

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document


  • Anindya SarkarUniversity of Calcutta

  • Vishwarkarma Singh

  • Pratim Ghosh

  • Bangalore S. Manjunath

  • Ambuj Singh

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free