An HEVC Compressed Domain Content-Based Video Signature For Copy Detection and Video Retrieval

被引:0
|
作者
Tahboub, Khalid [1 ]
Gadgil, Neeraj J. [1 ]
Comer, Mary L. [1 ]
Delp, Edward J. [1 ]
机构
[1] Purdue Univ, Sch Elect & Comp Engn, Video & Image Proc Lab VIPER, W Lafayette, IN 47907 USA
关键词
video signature; video fingerprint; copy detection; video search and retrieval; near-duplicate video; ROBUST; EFFICIENT; SEARCH;
D O I
10.1117/12.2040245
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Video sharing platforms and social networks have been growing very rapidly for the past few years. The rapid increase in the amount of video content introduces many challenges in terms of copyright violation detection and video search and retrieval. Generating and matching content-based video signatures, or fingerprints, is an effective method to detect copies or "near-duplicate" videos. Video signatures should be robust to changes in the video features used to characterize the signature caused by common signal processing operations. Recent work has focused on generating video signatures based on the uncompressed domain. However, decompression is a computationally intensive operation. In large video databases, it becomes advantageous to create robust signatures directly from the compressed domain. The High Efficiency Video Coding (HEVC) standard has been recently ratified as the latest video coding standard and wide spread adoption is anticipated. We propose a method in which a content-based video signature is generated directly from the HEVC-coded bitstream. Motion vectors from the HEVC-coded bitstream are used as the features. A robust hashing function based on projection on random matrices is used to generate the hashing bits. A sequence of these bits serves as the signature for the video. Our experimental results show that our proposed method generates a signature robust to common signal processing techniques such as resolution scaling, brightness scaling and compression.
引用
收藏
页数:13
相关论文
共 50 条
  • [41] A systematic review on content-based video retrieval
    Spolaor, Newton
    Lee, Huei Diana
    Resende Takaki, Weber Shoity
    Ensina, Leandro Augusto
    Rodrigues Coy, Claudio Saddy
    Wu, Feng Chung
    [J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2020, 90
  • [42] Scene change detection algorithms for content-based video indexing and retrieval
    Fernando, WAC
    Canagarajah, CN
    Bull, DR
    [J]. ELECTRONICS & COMMUNICATION ENGINEERING JOURNAL, 2001, 13 (03): : 117 - 126
  • [43] Flexible video coding scheme for content-based video storage and retrieval
    Zhang, Jianning
    Sun, Lifeng
    Yang, Shiqiang
    Zhong, Yuzhuo
    [J]. 12TH INTERNATIONAL MULTI-MEDIA MODELLING CONFERENCE PROCEEDINGS, 2006, : 66 - 71
  • [44] MotionSearch: Content-Based Video Retrieval and Activity Recognition in Video Surveillance
    Schonfeld, Dan
    [J]. AVSS: 2009 6TH IEEE INTERNATIONAL CONFERENCE ON ADVANCED VIDEO AND SIGNAL BASED SURVEILLANCE, 2009, : 194 - 194
  • [45] Content-based image indexing and retrieval in compressed domain
    Jiang, J
    [J]. ADVANCES IN MODELLING, ANIMATION AND RENDERING, 2002, : 39 - 64
  • [46] Detection of frame deletion in HEVC-Coded video in the compressed domain
    Hong, Jin Hyung
    Yang, Yoonmo
    On, Byung Tae
    [J]. DIGITAL INVESTIGATION, 2019, 30 : 23 - 31
  • [47] Abnormal Event Detection in Surveillance Video: A Compressed Domain Approach for HEVC
    Zhang, Yihao
    Chao, Hongyang
    [J]. 2017 DATA COMPRESSION CONFERENCE (DCC), 2017, : 475 - 475
  • [48] ViCopT: a robust system for content-based video copy detection in large databases
    Julien Law-To
    Olivier Buisson
    Valerie Gouet-Brunet
    Nozha Boujemaa
    [J]. Multimedia Systems, 2009, 15 : 337 - 353
  • [49] A Robust and Fast Video Copy Detection System Using Content-Based Fingerprinting
    Esmaeili, Mani Malek
    Fatourechi, Mehrdad
    Ward, Rabab Kreidieh
    [J]. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2011, 6 (01) : 213 - 226
  • [50] ViCopT: a robust system for content-based video copy detection in large databases
    Law-To, Julien
    Buisson, Olivier
    Gouet-Brunet, Valerie
    Boujemaa, Nozha
    [J]. MULTIMEDIA SYSTEMS, 2009, 15 (06) : 337 - 353