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Modelling eye movements during Multiple Object Tracking
Název práce v češtině: Modelling eye movements during Multiple Object Tracking
Název v anglickém jazyce: Modelling eye movements during Multiple Object Tracking
Klíčová slova: modely, oční pohyby, sledování více objektů, neuronové sítě
Klíčová slova anglicky: models, eye movements, multiple object tracking, neural networks
Akademický rok vypsání: 2011/2012
Typ práce: diplomová práce
Jazyk práce: angličtina
Ústav: Katedra softwaru a výuky informatiky (32-KSVI)
Vedoucí / školitel: Mgr. Jiří Lukavský, Ph.D.
Řešitel: skrytý - zadáno a potvrzeno stud. odd.
Datum přihlášení: 31.10.2011
Datum zadání: 04.11.2011
Datum potvrzení stud. oddělením: 12.12.2011
Datum a čas obhajoby: 03.09.2012 10:00
Datum odevzdání elektronické podoby:05.07.2012
Datum odevzdání tištěné podoby:30.07.2012
Datum proběhlé obhajoby: 03.09.2012
Oponenti: Mgr. Peter Gabriel Toth
Zásady pro vypracování
People tend to move their eyes towards the objects of their interest. However, when they are asked to pay attention to several objects at once, it is not clear how they are optimizing their eye movements with respect to the positions of the objects and the distances to the other objects within the scene (distractors).
In a typical Multiple Object Tracking experiment a person watches a screen with 8 identical dots. Four dots are highlighted for 2 seconds, and then they turn gray and all dots start to move for 10 seconds. Finally, the motion stops and the person is asked to identify the previously highlighted dots. The task has been used for many experiments on spatial attention in psychology, but in combination with computer-based eye tracking it provides also an interesting challenge for computer scientists. Only few studies so far attempted to model eye movements in this dynamic task, while there are several models designed for static attentional tasks (e.g. visual search).
Goal of the project is to design one or several models of eye movements during Multiple Object Tracking, based on the empirical data and literature. For this purpose it will be necessary to design, implement and evaluate an eye tracking experiment. The eye movement predictions of the proposed model/s will be evaluated in a subsequent experiment, and the performance will be compared with other models.
Seznam odborné literatury
Mitchell, T.M. (1997). Machine Learning; MIT Press.
Russell, S.J., Norvig, P. (1995). Artificial Intelligence: A Modern Approach; Prentice Hall.
Pylyshyn, Z. W., & Storm, R. W. (1988). Tracking multiple independent targets: evidence for a parallel tracking mechanism. Spatial Vision, 3(3), 179–197.
Cavanagh, P., & Alvarez, G. A. (2005). Tracking multiple targets with multifocal attention. Trends in Cognitive Sciences, 9(7), 349–354.
Colas, F., Flacher, F., Tanner, T., Bessière, P., & Girard, B. (2009). Bayesian models of eye movement selection with retinotopic maps. Biological Cybernetics, 100(3), 203–214.
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