A robust and lightweight feature system for video fingerprinting

Tzu Jui Liu*, Hye Jung Han, Xin Xin, Zhu Li, Aggelos K Katsaggelos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

In this paper, a new content-based feature identification method for video sequences is presented. It is robust to a number of image transformations and relatively lightweight compare to most state of the art methods. A scale and rotation invariant descriptor for a set of interest points in detected key frames is proposed based on modified minimal spanning tree algorithm. In addition, a predicative coding scheme is used to achieve minimal size of the descriptor for transmission. Furthermore, the pairwise distance between the frequency responses of the curvature vector from the descriptors is calculated and compared to efficiently match query with a large database. Experimental results demonstrate the effectiveness of our approach.

Original languageEnglish (US)
Title of host publicationProceedings of the 20th European Signal Processing Conference, EUSIPCO 2012
Pages160-164
Number of pages5
StatePublished - Nov 27 2012
Event20th European Signal Processing Conference, EUSIPCO 2012 - Bucharest
Duration: Aug 27 2012Aug 31 2012

Other

Other20th European Signal Processing Conference, EUSIPCO 2012
CityBucharest
Period8/27/128/31/12

Keywords

  • content-based fingerprinting
  • multimedia fingerprinting
  • Robust video hashing
  • video copy detection

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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