VIDEO SUMMARIZATION BASED ON LOCAL FEATURES

被引:0
|
作者
Massaoudi, Mohamed [1 ]
Bahroun, Sahbi [1 ]
Zagrouba, Ezzeddine [1 ]
机构
[1] Univ Tunis El Manar, Inst Super Informat ISI, Res Team Intelligent Syst Imaging & Artificial Vi, LIMTIC Lab, 2 Rue Abou Rayhane Bayrouni, Ariana 2080, Tunisia
来源
25. INTERNATIONAL CONFERENCE IN CENTRAL EUROPE ON COMPUTER GRAPHICS, VISUALIZATION AND COMPUTER VISION (WSCG 2017) | 2017年 / 2701卷
关键词
Video Summarization; Keyframe Extraction; Interest Points; SURF; FLANN;
D O I
暂无
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Keyframe extraction process consists on presenting an abstract of the entire video with the most representative frames. It is one of the basic procedures relating to video retrieval and summary. This paper present a novel method for keyframe extraction based on SURF local features. First, we select a group of candidate frames from a video shot using a leap extraction technique. Then, SURF is used to detect and describe local features on the candidate frames. After that, we analyzed those features to eliminate near duplicate keyframes, helping to keep a compact set, using FLANN method. We developed a comparative study to evaluate our method with three state of the art approaches based on local features. The results show that our method overcomes those approaches.
引用
收藏
页码:13 / 17
页数:5
相关论文
共 50 条
  • [1] Online Video Summarization Based on Local Features
    Iparraguirre, Javier
    Delrieux, Claudio A.
    INTERNATIONAL JOURNAL OF MULTIMEDIA DATA ENGINEERING & MANAGEMENT, 2014, 5 (02): : 41 - 53
  • [2] Video Summarization with Global and Local Features
    Guan, Genliang
    Wang, Zhiyong
    Yu, Kaimin
    Mei, Shaohui
    He, Mingyi
    Feng, Dagan
    2012 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO WORKSHOPS (ICMEW), 2012, : 570 - 575
  • [3] Speeded-up Video Summarization Based on Local Features
    Iparraguirre, Javier
    Delrieux, Claudio
    2013 IEEE INTERNATIONAL SYMPOSIUM ON MULTIMEDIA (ISM), 2013, : 370 - 373
  • [4] Key Frames Extraction Based on Local Features for Efficient Video Summarization
    Gharbi, Hana
    Massaoudi, Mohamed
    Bahroun, Sahbi
    Zagrouba, Ezzeddine
    ADVANCED CONCEPTS FOR INTELLIGENT VISION SYSTEMS, ACIVS 2016, 2016, 10016 : 275 - 285
  • [5] Video Summarization Based on Multimodal Features
    Zhang, Yu
    Liu, Ju
    Liu, Xiaoxi
    Gao, Xuesong
    INTERNATIONAL JOURNAL OF MULTIMEDIA DATA ENGINEERING & MANAGEMENT, 2020, 11 (04): : 60 - 76
  • [6] Multimodal Video Summarization based on Fuzzy Similarity Features
    Psallidas, Theodoros
    Vasilakakis, Michael D.
    Spyrou, Evaggelos
    Iakovidis, Dimitris K.
    2022 IEEE 14TH IMAGE, VIDEO, AND MULTIDIMENSIONAL SIGNAL PROCESSING WORKSHOP (IVMSP), 2022,
  • [7] Video Summarization Method Based on the Weber Local Descriptor
    Cirne, Marcos Vinicius Mussel
    Pedrini, Helio
    2017 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2017, : 1304 - 1309
  • [8] Video Summarization with Visual and Semantic Features
    Dong, Pei
    Wang, Zhiyong
    Zhuo, Li
    Feng, Dagan
    ADVANCES IN MULTIMEDIA INFORMATION PROCESSING-PCM 2010, PT I, 2010, 6297 : 203 - +
  • [9] Unsupervised video summarization using deep Non-Local video summarization networks
    Zang, Sha-Sha
    Yu, Hui
    Song, Yan
    Zeng, Ru
    NEUROCOMPUTING, 2023, 519 : 26 - 35
  • [10] Local Binary Pattern based Shot Boundary Detection for Video Summarization
    Kaavya, S.
    Priya, Lakshmi G. G.
    2017 SECOND INTERNATIONAL CONFERENCE ON RECENT TRENDS AND CHALLENGES IN COMPUTATIONAL MODELS (ICRTCCM), 2017, : 165 - 169