short-paper

Temporal spectral residual: fast motion saliency detection

Authors:

Xinyi Cui,

Qingshan Liu,

Dimitris MetaxasAuthors Info & Claims

MM '09: Proceedings of the 17th ACM international conference on Multimedia

Pages 617 - 620

https://doi.org/10.1145/1631272.1631370

Published: 19 October 2009 Publication History

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Abstract

Saliency detection has attracted much attention in recent years. It aims at locating semantic regions in images for further image understanding. In this paper, we address the issue of motion saliency detection for video content analysis. Inspired by the idea of Spectral Residual for image saliency detection, we propose a new method Temporal Spectral Residual on video slices along X-T and Y-T planes, which can automatically separate foreground motion objects from backgrounds, also with the help of threshold selection and voting schemes. Different from conventional background modeling methods with complex mathematical model, the proposed method is only based on Fourier spectrum analysis, so it is simple and fast. The power of our proposed method is demonstrated in the experiments of four typical videos with different dynamic background.

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Hui WZhu ZZheng SZhao Y(2024)Endow SAM with Keen Eyes: Temporal-Spatial Prompt Learning for Video Camouflaged Object Detection2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52733.2024.01803(19058-19067)Online publication date: 16-Jun-2024
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Gharahbagh AHajihashemi VFerreira MMachado JTavares J(2024)Hybrid time-spatial video saliency detection method to enhance human action recognition systemsMultimedia Tools and Applications10.1007/s11042-024-18126-x83:30(74053-74073)Online publication date: 14-Feb-2024
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Index Terms

Temporal spectral residual: fast motion saliency detection
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks
        Video summarization

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Information

Published In

MM '09: Proceedings of the 17th ACM international conference on Multimedia

October 2009

1202 pages

ISBN:9781605586083

DOI:10.1145/1631272

General Chairs:
Wen Gao
Peking University, China
,
Yong Rui
Microsoft, China
,
Alan Hanjalic
Delft University of Technology, The Netherlands
,
Program Chairs:
Changsheng Xu
Institute of Automation, Chinese Academy of Sciences, China
,
Eckehard Steinbach
Technical University of Munich, Germany
,
Abdulmotaleb El Saddik
University of Ottawa, Canada
,
Michelle Zhou
IBM T. J. Watson Research Center, USA

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 October 2009

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MM09

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MM09: ACM Multimedia Conference

October 19 - 24, 2009

Beijing, China

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Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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HAN YHe XZHANG HZUO YZHANG WAi QCHEN Z(2024)Metaverse Framework Designing for Energy Scheduling in Energy Internet of Things Considering EmergenceDigital Twin10.12688/digitaltwin.17873.23(6)Online publication date: 26-Jul-2024
https://doi.org/10.12688/digitaltwin.17873.2
Hui WZhu ZZheng SZhao Y(2024)Endow SAM with Keen Eyes: Temporal-Spatial Prompt Learning for Video Camouflaged Object Detection2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52733.2024.01803(19058-19067)Online publication date: 16-Jun-2024
https://doi.org/10.1109/CVPR52733.2024.01803
Gharahbagh AHajihashemi VFerreira MMachado JTavares J(2024)Hybrid time-spatial video saliency detection method to enhance human action recognition systemsMultimedia Tools and Applications10.1007/s11042-024-18126-x83:30(74053-74073)Online publication date: 14-Feb-2024
https://doi.org/10.1007/s11042-024-18126-x
HAN YHe XZHANG HZUO YZHANG WAi QCHEN Z(2023)Metaverse Framework Designing for Energy Scheduling in Energy Internet of Things Considering EmergenceDigital Twin10.12688/digitaltwin.17873.13(6)Online publication date: 7-Aug-2023
https://doi.org/10.12688/digitaltwin.17873.1
Kocak AErdem EErdem A(2022)A Gated Fusion Network for Dynamic Saliency PredictionIEEE Transactions on Cognitive and Developmental Systems10.1109/TCDS.2021.309497414:3(995-1008)Online publication date: Sep-2022
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Zabihi STavakoli HBorji AMansoori E(2022)A compact deep architecture for real-time saliency predictionSignal Processing: Image Communication10.1016/j.image.2022.116671104(116671)Online publication date: May-2022
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Khan UZhang XSu Y(2021)Active Contour Model Using Fast Fourier Transformation for Salient Object DetectionElectronics10.3390/electronics1002019210:2(192)Online publication date: 15-Jan-2021
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Wu ZSu LHuang Q(2019)Learning Coupled Convolutional Networks Fusion for Video Saliency PredictionIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2018.287095429:10(2960-2971)Online publication date: Oct-2019
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Sun ZWang XZhang QJiang J(2019)Real-Time Video Saliency Prediction Via 3D Residual Convolutional Neural NetworkIEEE Access10.1109/ACCESS.2019.29464797(147743-147754)Online publication date: 2019
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Wu XLu XLeung H(2019)A motion and lightness saliency approach for forest smoke segmentation and detectionMultimedia Tools and Applications10.1007/s11042-019-08047-5Online publication date: 9-Aug-2019
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Temporal Spectral Residual for fast salient motion detection

Motion Analysis Based on Spatial-Temporal Visual Attention

Automatic spectral video matting

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