article

A visual attention model for adapting images on small displays

Authors:

Hong-Jiang Zhang,

He-Qin ZhouAuthors Info & Claims

Multimedia Systems, Volume 9, Issue 4

Pages 353 - 364

https://doi.org/10.1007/s00530-003-0105-4

Published: 01 October 2003 Publication History

Abstract

Image adaptation, one of the essential problems in adaptive content delivery for universal access, has been actively explored for some time. Most existing approaches have focused on generic adaptation with a view to saving file size under constraints in client environment and have hardly paid attention to user perceptions of the adapted result. Meanwhile, the major limitation on the user's delivery context is moving away from data volume (or time-to-wait) to screen size because of the galloping development of hardware technologies. In this paper, we propose a novel method for adapting images based on user attention. A generic and extensible image attention model is introduced based on three attributes (region of interest, attention value, and minimal perceptible size) associated with each attention object. A set of automatic modeling methods are presented to support this approach. A branch-and-bound algorithm is also developed to find the optimal adaptation efficiently. Experimental results demonstrate the usefulness of the proposed scheme and its potential application in the future.

References

[1]

Chandra S, Gehani A, Ellis CS, Vahdat A (2001) Transcoding characteristics of Web images. Proc SPIE (Multimedia Comput Network 2001) 4312:135-149

[2]

Chen JL, Zhou BY, Shi J, Zhang HJ, Wu QF (2001) Function-based object model towards website adaptation. In: Proceedings of the 10th international World Wide Web conference, Hong Kong, May 2001, pp 587-596

Digital Library

[3]

Chen XR, Zhang HJ (2001) Text area detection from video frames. In: Proceedings of the 2nd IEEE Pacific-Rim conference on multimedia (PCM2001), Beijing, October 2001, pp 222-228

[4]

Christopoulos C, Skodras A, Ebrahimi T (2000) The JPEG2000 still image coding system: an overview. IEEE Trans Consumer Electron 46(4):1103-1127

Digital Library

[5]

Fan X, Xie X, Ma WY, Zhang HJ, Zhou HQ (2003) Visual attention based image browsing on mobile devices. In: Proceedings of the IEEE international conference on multimedia and expo (ICME 03), Baltimore, July 2003

[6]

Fox A, Gribble S, Brewer EA, Amir E (1996) Adapting to network and client variability via on-demand dynamic distillation. In: Proceedings of the 7th international conference on architectural support for programming languages and operating systems. Cambridge, MA, October 1996, pp 160-170

Digital Library

[7]

Han R, Bhagwat P, Lamaire R, Mummert T, Perret V, Rubas J (1998) Dynamic adaptation in an image transcoding proxy for mobile Web access. IEEE Pers Commun 5(6):8-17

[8]

ISO/IEC JTC1/SC29/WG11/N4242 (2001) ISO/IEC 15938-5 FDIS Information technology - multimedia content description interface - Part 5: Multimedia description schemes. Sydney, July 2001

[9]

ISO/IEC JTC1/SC29/WG11/N4674 (2002) MPEG-7 Overview. Jeju, Korea, March 2002

[10]

ISO/IEC JTC1/SC29/WG11/N4819 (2002) MPEG-21 Digital item adaptation. Fairfax, VA, May 2002

[11]

Itti L, Koch C, Niebur E (1998) A model of saliency-based visual attention for rapid scene analysis. IEEE Trans Pattern Analysis Mach Intell 20(11):1254-1259

Digital Library

[12]

Itti L, Koch C (1999) A comparison of feature combination strategies for saliency-based visual attention system. Proc SPIE (Hum Vis Electron Imag IV) 3644:473-482

[13]

Itti L, Koch C (2001) Computational modeling of visual attention. Nat Rev Neurosci 2(3):194-203

[14]

Lee K, Chang HS, Chun SS, Choi L, Sull S (2001) Perception-based image transcoding for universal multimedia access. In: Proceedings of the 8th international conference on image processing (ICIP-2001), Thessaloniki, Greece, October 2001, 2:475-478

[15]

Li SZ, Zhu L, Zhang ZQ, Blake A, Zhang HJ, Shum H (2002) Statistical learning of multi-view face detection. In: Proceedings of the 7th European conference on computer vision (ECCV 2002), Copenhagen, May 2002, 4:67-81

[16]

Ma WY, Bedner I, Chang G, Kuchinsky A, Zhang HJ (2000) A framework for adaptive content delivery in heterogeneous network environments. Proc SPIE (Multimedia Comput Network 2000) 3969:86-100

[17]

Ma YF, Lu L, Zhang HJ, Li MJ (2002) A user attention model for video summarization. In: Proceedings of the 10th ACM international conference on multimedia, Juan-les-Pins, France, December 2002, pp 533-542

[18]

Mohan R, Smith JR, Li CS (1999) Adapting multimedia internet content for universal access. IEEE Trans Multimedia 1(1):104-114

Digital Library

[19]

Salah AA, Alpaydin E, Akarun L (2002) A selective attention-based method for visual pattern recognition with application to handwritten digit recognition and face recognition. IEEE Trans Pattern Analysis Mach Intell 24(3):420-425

Digital Library

[20]

Smith JR, Mohan R, Li CS (1998) Content-based transcoding of images in the Internet. In: Proceedings of the 5th international conference on image processing (ICIP-98), Chicago, October 1998, 3:7-11

[21]

World Wide Web Consortium (1999) Web content accessibility guidelines 1.0. May 1999, http://www.w3.org/tr/wai-webcontent/

Cited By

Pan ZCui JWang KWu YCao Z(2024)Pseudo Label Fusion With Uncertainty Estimation for Semi-Supervised Cropping Box RegressionIEEE Transactions on Multimedia10.1109/TMM.2024.337712526(8157-8171)Online publication date: 13-Mar-2024
https://dl.acm.org/doi/10.1109/TMM.2024.3377125
Pan ZChen YZhang JLu HCao ZZhong WWilliams BChen YNeville J(2023)Find beauty in the rareProceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v37i2.25293(2011-2019)Online publication date: 7-Feb-2023
https://dl.acm.org/doi/10.1609/aaai.v37i2.25293
Avidan SShamir A(2023)Seam Carving for Content-Aware Image ResizingSeminal Graphics Papers: Pushing the Boundaries, Volume 210.1145/3596711.3596776(609-617)Online publication date: 1-Aug-2023
https://dl.acm.org/doi/10.1145/3596711.3596776
Show More Cited By

Recommendations

Perceived interest and overt visual attention in natural images

Region of interest (ROI) based image and video processing has attracted increased research efforts in recent years. The concept of perceptual ROI, however, is not always clearly defined leading to different interpretations between researchers related to ...
Image information and visual quality

Measurement of visual quality is of fundamental importance to numerous image and video processing applications. The goal of quality assessment (QA) research is to design algorithms that can automatically assess the quality of images or videos in a ...
Region-based visual attention analysis with its application in image browsing on small displays
MM '07: Proceedings of the 15th ACM international conference on Multimedia

Visual attention has been a hot research point for many years and many new applications are emerging especially for wireless multimedia services. In this paper a novel region-based visual attention is proposed to detect the Regions of Interest (ROI) of ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Multimedia Systems

Multimedia Systems Volume 9, Issue 4

October 2003

84 pages

ISSN:0942-4962

Issue’s Table of Contents

Copyright © Copyright © 2003 Springer-Verlag.

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 October 2003

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

116
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 18 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Pan ZCui JWang KWu YCao Z(2024)Pseudo Label Fusion With Uncertainty Estimation for Semi-Supervised Cropping Box RegressionIEEE Transactions on Multimedia10.1109/TMM.2024.337712526(8157-8171)Online publication date: 13-Mar-2024
https://dl.acm.org/doi/10.1109/TMM.2024.3377125
Pan ZChen YZhang JLu HCao ZZhong WWilliams BChen YNeville J(2023)Find beauty in the rareProceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v37i2.25293(2011-2019)Online publication date: 7-Feb-2023
https://dl.acm.org/doi/10.1609/aaai.v37i2.25293
Avidan SShamir A(2023)Seam Carving for Content-Aware Image ResizingSeminal Graphics Papers: Pushing the Boundaries, Volume 210.1145/3596711.3596776(609-617)Online publication date: 1-Aug-2023
https://dl.acm.org/doi/10.1145/3596711.3596776
Ayubi JAmirani MValizadeh M(2022)A New Seam Carving Method for Image Resizing Based on Entropy Energy and Lyapunov ExponentMultimedia Tools and Applications10.1007/s11042-022-13823-x82:13(19417-19440)Online publication date: 24-Nov-2022
https://dl.acm.org/doi/10.1007/s11042-022-13823-x
Li XZhang GWu YLi XZhang Y(2022)Rule of thirds-aware reinforcement learning for image aesthetic croppingThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-022-02687-939:11(5651-5667)Online publication date: 10-Oct-2022
https://dl.acm.org/doi/10.1007/s00371-022-02687-9
Mishra AScharfenberger CSiva PLi FWong AClausi D(2021)DESIRe: Discontinuous energy seam carving for image retargeting via structural and textural energy functionals2015 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP.2015.7351494(3695-3699)Online publication date: 9-Mar-2021
https://dl.acm.org/doi/10.1109/ICIP.2015.7351494
Mishra AScharfenberger CSiva PLi FWong AClausi D(2021)DESIRe: Discontinuous energy seam carving for image retargeting via structural and textural energy functionals2015 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP.2015.7351492(3685-3689)Online publication date: 9-Mar-2021
https://dl.acm.org/doi/10.1109/ICIP.2015.7351492
Zhu LCao XFang YZhang LLi X(2020)Application of Visual Saliency in the Background Image Cutting for Layout DesignSocial Computing and Social Media. Design, Ethics, User Behavior, and Social Network Analysis10.1007/978-3-030-49570-1_12(168-183)Online publication date: 19-Jul-2020
https://dl.acm.org/doi/10.1007/978-3-030-49570-1_12
Arya RAgrawal RSingh N(2019)A novel approach for salient object detection using double-density dual-tree complex wavelet transform in conjunction with superpixel segmentationKnowledge and Information Systems10.1007/s10115-018-1243-560:1(327-361)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/s10115-018-1243-5
Park EHan JKim KCho Ydel Pobil A(2018)Effects of Screen Size in Mobile Learning Over TimeProceedings of the 12th International Conference on Ubiquitous Information Management and Communication10.1145/3164541.3164625(1-5)Online publication date: 5-Jan-2018
https://dl.acm.org/doi/10.1145/3164541.3164625
Show More Cited By

View Options

View options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Issue’s Table of Contents