Eye Movements Show Optimal Average Anticipation with Natural Dynamic Scenes
- 196 Downloads
A less studied component of gaze allocation in dynamic real-world scenes is the time lag of eye movements in responding to dynamic attention-capturing events. Despite the vast amount of research on anticipatory gaze behaviour in natural situations, such as action execution and observation, little is known about the predictive nature of eye movements when viewing different types of natural or realistic scene sequences. In the present study, we quantify the degree of anticipation during the free viewing of dynamic natural scenes. The cross-correlation analysis of image-based saliency maps with an empirical saliency measure derived from eye movement data reveals the existence of predictive mechanisms responsible for a near-zero average lag between dynamic changes of the environment and the responding eye movements. We also show that the degree of anticipation is reduced when moving away from natural scenes by introducing camera motion, jump cuts, and film-editing.
KeywordsEye movements Anticipatory gaze behaviour Natural dynamic scenes Saliency maps
We would like to thank Karl Gegenfurtner: data were collected in his lab at the Dept. of Psychology of Giessen University. Our research has received funding from the European Commission within the project GazeCom (contract no. IST-C-033816, http://www.gazecom.eu) of the 6th Framework Programme. All views expressed herein are those of the authors alone; the European Community is not liable for any use made of the information.
- 1.Barth E, Dorr M, Böhme M, Gegenfurtner KR, Martinetz T. Guiding the mind’s eye: improving communication and vision by external control of the scanpath. In: Rogowitz BE, Pappas TN, Daly SJ, editors. Human vision and electronic imaging, vol 6057 of Proceedings of SPIE. Invited contribution for a special session on Eye Movements, Visual Search, and Attention: a Tribute to Larry Stark; 2006.Google Scholar
- 2.Becker W. Saccades. In: Carpenter RHS, editor. Vision & visual dysfunction, vol 8: Eye movements. London: CRC Press; 1991. p. 95–137.Google Scholar
- 5.Carpenter RHS. Oculomotor procrastination. In: Fisher DF, Monty RA, Senders JW, editors. Eye movements: cognition and visual perception. Hillsdale, NJ: Lawrence Erlbaum; 1981. p. 237–46.Google Scholar
- 7.Crundall D, Chapman P, Phelps N, Underwood G. Eye movements and hazard perception in police pursuit and emergency response driving. J Exp Psychol. 2003;9(3):163–74.Google Scholar
- 12.Gonzalez RC, Woods RE. Digital image processing, 2nd edn. Boston, MA: Addison-Wesley Longman Publishing Co., Inc; 2001.Google Scholar
- 28.Smith TJ, Henderson JM. Edit blindness: the relationship between attention and global change blindness in dynamic scenes. J Eye Movement Res. 2008;2(2):1–17.Google Scholar
- 33.Vig E, Dorr M, Martinetz T, Barth E. A learned saliency predictor for dynamic natural scenes. In: Diamantaras K, Duch W, Iliadis LS, editors. ICANN 2010, Part III, LNCS 6354, Berlin: Springer; 2010. p. 52–61.Google Scholar