Abstract
Masciocchi and Still [1] suggested that biologically inspired computational saliency models could predict attentional deployment within webpages. Their stimuli were presented on a large desktop monitor. We explored whether a saliency model’s predictive performance can be applied to small mobile interface displays. We asked participants to free-view screenshots of NASA’s mobile application Playbook. The Itti et al. [2] saliency model was employed to produce the predictive stimulus-driven maps. The first six fixations were used to select values to form the saliency maps’ bins, which formed the observed distribution. This was compared to the shuffled distribution, which offers a very conservative chance comparison as it includes predictable spatial biases by using a within-subjects bootstrapping technique. The observed distribution values were higher than the shuffled distribution. This suggests that a saliency model was able to predict the deployment of attention within small mobile application interfaces.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Masciocchi, C.M., Still, J.D.: Alternative to eye tracking for predicting stimulus-driven attentional selection within interfaces. J. Hum.-Comput. Interact. 34, 285–301 (2013)
Itti, L., Koch, C., Niebur, E.: A model of saliency-based fast visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Mach. Intell. 20, 1254–1259 (1998)
Theeuwes, J.: Top-down search strategies cannot override attentional capture. Psychon. Bull. Rev. 11, 65–70 (2004)
Wolfe, J.M.: Guided Search 4.0: Current Progress with a Model of Visual Search. In: Gray, W. (eds.) Integrated Models of Cognitive Systems, pp. 99–119, New York, Oxford (2007)
Theeuwes, J.: Perceptual selectivity for color and form. Percept. Psychophys. 51, 599–606 (1992)
Parkhurst, D., Law, K., Niebur, E.: Modeling the role of salience in the allocation of overt visual attention. Vis. Res. 42, 107–123 (2002)
Still, J.D., Masciocchi, C.M.: A saliency model predicts fixations in web interfaces. In: 5th International Workshop on Model Driven Development of Advanced User Interfaces Computer-Human Interaction Conference, pp. 25–29 (2010)
Jones, M., Marsden, G., Mohd-Nasir, N., Boone, K., Buchanan, G.: Improving web interaction on small displays. J. Comput. Netw. 31, 1129–1137 (1999)
Christie, J., Klein, R.M., Watters, C.: A comparison of simple hierarchy and grid metaphor for option layouts on small-size screens. Int. J. Hum.-Comput. Stud. 60, 564–584 (2004)
Garcia-Lopez, E., Garcia-Cabot, A., de-Marcos, L.: An experiment with content distribution methods in touchscreen mobile devices. J. Appl. Ergon. 50, 79–85 (2015)
Lim, J.J., Feria, C.: Visual search on a mobile device while walking. In: Mobile HCI Conference, pp. 295–304, San Francisco, CA (2012)
Watters, C., Duffy, J., Duffy, K.: Using large tables on small display devices. Int. J. Hum.-Comput. Stud. 58, 21–37 (2003)
Marquez, J.J., Pyrzak, G., Hashemi, S., Ahmed, S., McMillin, K., Medwid, J., Chen, D., Esten, H.: Supporting real-time operations and execution through timeline and scheduling aids. In: 43rd International Conference on Environmental Systems, pp. 1–11. ICES (2013)
Harel, J., Koch, C., Perona, P.: Graph-based visual saliency. In: NIPS, vol. 1, pp. 5–12 (2006)
Rosenholtz, R., Dorai, A., Freeman, R.: Do predictions of visual perception aid design? ACM Trans. Appl. Percept. 8, 1–20 (2011)
Acknowledgments
The authors thank Steven Hillenius for providing access to the Playbook software through a demo site. In addition, we thank the Virginia Space Grant Consortium for financially supporting this research.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Still, J.D., Hicks, J., Cain, A., Billman, D. (2018). Predicting Stimulus-Driven Attentional Selection Within Mobile Interfaces. In: Baldwin, C. (eds) Advances in Neuroergonomics and Cognitive Engineering. AHFE 2017. Advances in Intelligent Systems and Computing, vol 586. Springer, Cham. https://doi.org/10.1007/978-3-319-60642-2_24
Download citation
DOI: https://doi.org/10.1007/978-3-319-60642-2_24
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-60641-5
Online ISBN: 978-3-319-60642-2
eBook Packages: EngineeringEngineering (R0)