A hybrid domain enhanced framework for video retargeting with spatial-temporal importance and 3D grid optimization

被引:3
|
作者
Wang, Jinqiao [1 ]
Xu, Min [2 ]
He, Xiangjian [2 ]
Lu, Hanqing [1 ]
Hoang, Doan [2 ]
机构
[1] Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100864, Peoples R China
[2] Univ Technol Sydney, Sch Comp & Commun, Sydney, NSW 2007, Australia
基金
中国国家自然科学基金;
关键词
Video retargeting; Visual attention; Visual concept; Spatial-temporal importance; 3D grid optimization;
D O I
10.1016/j.sigpro.2013.06.007
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
Recently, a ubiquitous video access is highly demanded for online video applications. One big challenge is that video service needs to adapt different device capabilities. Pervasive multimedia devices require an accurate and user comfort video retargeting. Letting users see their preferred content accurately directly affects their comforts. User preferences on video contents are different in various video domains. In this paper, we present a hybrid framework of video retargeting with a domain enhanced spatial-temporal grid optimization. First, we parse videos from low-level features to high-level visual concepts, combining with visual attention for an accurate importance description. Second, a semantic importance map is built up representing the spatial importance and temporal continuity, which is incorporated with a 3D rectilinear grid scaleplate to map frames to a target display, thereby keeping the aspect ratio of semantically salient objects as well as the perceptual coherency. Extensive evaluations are made on five typical video genres, i.e. sports, advertisements, lecture, news and surveillance. The comparison with the state-of-the-art approaches on both images and videos have demonstrated the advantages of the proposed approach. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:33 / 47
页数:15
相关论文
共 50 条
  • [1] A 3D wavelet based spatial-temporal approach for video watermarking
    Li, Y
    Gao, XB
    Ji, HB
    ICCIMA 2003: FIFTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND MULTIMEDIA APPLICATIONS, PROCEEDINGS, 2003, : 260 - 265
  • [2] Joint Spatial-Temporal Optimization for Stereo 3D Object Tracking
    Li, Peiliang
    Shi, Jieqi
    Shen, Shaojie
    2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2020, : 6876 - 6885
  • [3] A blind spatial-temporal algorithm based on 3D wavelet for video watermarking
    Zhuang, HY
    Li, Y
    Wu, CK
    2004 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXP (ICME), VOLS 1-3, 2004, : 1727 - 1730
  • [4] Modeling Spatial-Temporal Clues in a Hybrid Deep Learning Framework for Video Classification
    Wu, Zuxuan
    Wang, Xi
    Jiang, Yu-Gang
    Ye, Hao
    Xue, Xiangyang
    MM'15: PROCEEDINGS OF THE 2015 ACM MULTIMEDIA CONFERENCE, 2015, : 461 - 470
  • [5] c-Space: A Mobile Framework for the Visualization of Spatial-Temporal 3D Models
    Simoes, Bruno
    Marangon, Matteo
    De Amicis, Raffaele
    INTELLIGENT INTERACTIVE MULTIMEDIA SYSTEMS AND SERVICES, 2015, 40 : 35 - 45
  • [6] Spatial-temporal Concept based Explanation of 3D ConvNets
    Ji, Ying
    Wang, Yu
    Kato, Jien
    2023 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2023, : 15444 - 15453
  • [7] Spatial-Temporal Transformer for 3D Point Cloud Sequences
    Wei, Yimin
    Liu, Hao
    Xie, Tingting
    Ke, Qiuhong
    Guo, Yulan
    2022 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV 2022), 2022, : 657 - 666
  • [8] Spatial-Temporal Graph Enhanced DETR Towards Multi-Frame 3D Object Detection
    Zhang, Yifan
    Zhu, Zhiyu
    Hou, Junhui
    Wu, Dapeng
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2024, 46 (12) : 10614 - 10628
  • [9] Video-based driver action recognition via hybrid spatial-temporal deep learning framework
    Hu, Yaocong
    Lu, Mingqi
    Xie, Chao
    Lu, Xiaobo
    MULTIMEDIA SYSTEMS, 2021, 27 (03) : 483 - 501
  • [10] An Energy Efficiency Node Scheduling Model for Spatial-Temporal Coverage Optimization in 3D Directional Sensor Networks
    Han, Chong
    Sun, Lijuan
    Xiao, Fu
    Guo, Jian
    IEEE ACCESS, 2016, 4 : 4408 - 4419