Cited By
View all- Riche N(2016)Databases for Saliency Model EvaluationFrom Human Attention to Computational Attention10.1007/978-1-4939-3435-5_11(191-207)Online publication date: 30-Jun-2016
Influence of stimulus and viewing task types on a learning-based visual saliency model
Pages 271 - 274
Abstract
Learning-based approaches using actual human gaze data have been proven to be an efficient way to acquire accurate visual saliency models and attracted much interest in recent years. However, it still remains yet to be answered how different types of stimulus (e.g., fractal images, and natural images with or without human faces) and viewing tasks (e.g., free viewing or a preference rating task) affect learned visual saliency models. In this study, we quantitatively investigate how learned saliency models differ when using datasets collected in different settings (image contextual level and viewing task) and discuss the importance of choosing appropriate experimental settings.
References
[1]
Borji, A., and Itti, L. 2013. State-of-the-art in visual attention modeling. IEEE Trans. Pattern Anal. Machine Intell. 35, 1, 185--207.
[2]
Borji, A., Tavakoli, H. R., Sihite, D. N., and Itti, L. 2013. Analysis of scores, datasets, and models in visual saliency modeling. In Proc. ICCV2013, 921--928.
[3]
Bruce, N. D., and Tsotsos, J. K. 2009. Saliency, attention, and visual search: An information theoretic approach. Journal of vision 9, 3.
[4]
Cerf, M., Frady, E. P., and Koch, C. 2009. Faces and text attract gaze independent of the task: Experimental data and computer model. Journal of vision 9, 12.
[5]
Harel, J., Koch, C., and Perona, P. 2006. Graph-based visual saliency. In Proc. NIPS2006, 545--552.
[6]
Itti, L., Koch, C., and Niebur, E. 1998. A model of saliency-based visual attention for rapid scene analysis. IEEE Tram. Pattern Anal. Machine Intell. 20, 11, 1254--1259.
[7]
Johnson, R. A., and Wichern, D. W. 2002. Applied multivariate statistical analysis. Pearson.
[8]
Judd, T., Ehinger, K., Durand, F., and Torralba, A. 2009. Learning to predict where humans look. In Proc. ICCV2009, 2106--2113.
[9]
Kienzle, W., Wichmann, F. A., Schlkopf, B., and Franz, M. O. 2007. A nonparametric approach to bottom-up visual saliency. In Proc. NIPS2007, 689--696.
[10]
Kubota, H., Sugano, Y., Okabe, T., Sato, Y., Sugimoto, A., and Hiraki, K. 2012. Incorporating visual field characteristics into a saliency map. In Proc. ETRA2012, ACM, 333--336.
[11]
Le Meur, O., Le Callet, P., and Barba, D. 2007. Predicting visual fixations on video based on low-level visual features. Vision research 47, 19, 2483--2498.
[12]
Lienhart, R., and Maydt, J. 2002. An extended set of haar-like features for rapid object detection. In Proc. ICIP2002, 900--903.
[13]
Ramanathan, S., Katti, H., Sebe, N., Kankanhalli, M., and Chua, T.-S. 2010. An eye fixation database for saliency detection in images. In Proc. ECCV2010, 30--43.
[14]
Tsotsos, J. K. 1991. Is complexity theory appropriate for analyzing biological systems? Behavioral and Brain Sciences 14 (12), 770--773.
[15]
Xiao, J., Hays, J., Ehinger, K. A., Oliva, A., and Torralba, A. 2010. Sun database: Large-scale scene recognition from abbey to zoo. In Proc. CVPR2010, IEEE, 3485--3492.
[16]
Zhao, Q., and Koch, C. 2011. Learning a saliency map using fixated locations in natural scenes. Journal of vision 11, 3.
[17]
Zhao, Q., and Koch, C. 2012. Learning visual saliency by combining feature maps in a nonlinear manner using adaboost. Journal of Vision 12, 6.
[18]
Zhao, Q., and Koch, C. 2013. Learning saliency-based visual attention: A review. Signal Processing 93, 6, 1401--1407.
Index Terms
- Influence of stimulus and viewing task types on a learning-based visual saliency model
Recommendations
A dataset and evaluation methodology for visual saliency in video
ICME'09: Proceedings of the 2009 IEEE international conference on Multimedia and ExpoRecently, visual saliency has drawn great research interest in the field of computer vision and multimedia. Various approaches aiming at calculating visual saliency have been proposed. To evaluate these approaches, several datasets have been presented ...
A brief survey of visual saliency detection
AbstractSalient object detection models mimic the behavior of human beings and capture the most salient region/object from the images or scenes, this field contains many important applications in both computer vision and pattern recognition tasks. Despite ...
Multi-Task Rank Learning for Visual Saliency Estimation
Visual saliency plays an important role in various video applications such as video retargeting and intelligent video advertising. However, existing visual saliency estimation approaches often construct a unified model for all scenes, thus leading to ...
Comments
Information & Contributors
Information
Published In
March 2014
394 pages
Copyright © 2014 Owner/Author.
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 26 March 2014
Check for updates
Author Tags
Qualifiers
- Research-article
Funding Sources
Conference
Acceptance Rates
Overall Acceptance Rate 69 of 137 submissions, 50%
Upcoming Conference
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- View Citations1Total Citations
- 136Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 01 Mar 2025
Other Metrics
Citations
Cited By
View all- Riche N(2016)Databases for Saliency Model EvaluationFrom Human Attention to Computational Attention10.1007/978-1-4939-3435-5_11(191-207)Online publication date: 30-Jun-2016
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in