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A Compressed-domain Robust Descriptor for Near Duplicate Video Copy Detection

Published: 19 November 2014 Publication History

Abstract

This paper introduces a global descriptor from the compressed video domain (H.264) for near duplicate video copy detection tasks. The proposed descriptor uses a spatial-temporal feature structure in an ordinal pattern distribution format. The proposed descriptor is constructed from Intra-Prediction Modes (IPM) of key frames (IDR & I slices) and extracted from the compressed video files, using the MPEG4/AVC (H.264) codec. Intra-prediction is the compression technique used in the key frames of the H.264 codec. As the proposed feature describes pictures globally, this research compares the feature with the two other well-known global image descriptors, ordinal intensity/colour Histograms and ordinal Auto-correlograms, as baselines. Our experiments show how the proposed feature outperforms the baseline features in non-geometric transformations T3, T4 and T5 in effectiveness as well as efficiency. It is due to better representation of the image content and smaller feature vector size. The core competency of the proposed feature is in non-linear brightness and contrast changes (Gamma expansion and compression) in which the intensity/colour Histograms and Auto-correlograms are deficient.

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Cited By

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  • (2020)A systematic review on content-based video retrievalEngineering Applications of Artificial Intelligence10.1016/j.engappai.2020.10355790:COnline publication date: 29-Jun-2020
  • (2015)Evaluating Spatio-Temporal Parameters in Video Similarity Detection by Global Descriptors2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA)10.1109/DICTA.2015.7371255(1-8)Online publication date: Nov-2015
  • (2015)Enhanced-IPMH as a Robust Visual Descriptor from H.264/AVC and Evaluation of Parameters Effects2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA)10.1109/DICTA.2015.7371254(1-8)Online publication date: Nov-2015

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  1. A Compressed-domain Robust Descriptor for Near Duplicate Video Copy Detection

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      cover image ACM Other conferences
      IVCNZ '14: Proceedings of the 29th International Conference on Image and Vision Computing New Zealand
      November 2014
      298 pages
      ISBN:9781450331845
      DOI:10.1145/2683405
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Publication History

      Published: 19 November 2014

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      Author Tags

      1. Compressed domain
      2. Content-based Copy Detection
      3. Global descriptors
      4. H.264
      5. Intra-prediction
      6. MPEG-4 AVC
      7. Near-duplicate video copy detection
      8. Non-linear brightness and contrast changes

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      IVCNZ '14 Paper Acceptance Rate 55 of 74 submissions, 74%;
      Overall Acceptance Rate 55 of 74 submissions, 74%

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      Cited By

      View all
      • (2020)A systematic review on content-based video retrievalEngineering Applications of Artificial Intelligence10.1016/j.engappai.2020.10355790:COnline publication date: 29-Jun-2020
      • (2015)Evaluating Spatio-Temporal Parameters in Video Similarity Detection by Global Descriptors2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA)10.1109/DICTA.2015.7371255(1-8)Online publication date: Nov-2015
      • (2015)Enhanced-IPMH as a Robust Visual Descriptor from H.264/AVC and Evaluation of Parameters Effects2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA)10.1109/DICTA.2015.7371254(1-8)Online publication date: Nov-2015

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