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Visual interestingness in image sequences


Grabner, Helmut; Nater, Fabian; Druey, Michel D; Van Gool, Luc (2013). Visual interestingness in image sequences. In: Proceedings ACM International Conference on Multimedia, New York, 21 October 2013 - 25 October 2013, 1017-1026.

Abstract

Interestingness is said to be the power of attracting or holding one's attention (because something is unusual or exciting, etc.). We, as humans, have the great capacity to direct our visual attention and judge the interestingness of a scene. Consider for example the image sequence in the figure on the right. The spider in front of the camera or the snow on the lens are examples of events that deviate from the context since they violate the expectations, and therefore are considered interesting. On the other hand, weather changes or a camera shift, do not raise human attention considerably, even though large regions of the image are influenced. In this work we firstly investigate what humans consider as "interesting" in image sequences. Secondly we propose a computer vision algorithm to automatically spot these interesting events. To this end, we integrate multiple cues inspired by cognitive concepts and discuss why and to what extent the automatic discovery of visual interestingness is possible.

Abstract

Interestingness is said to be the power of attracting or holding one's attention (because something is unusual or exciting, etc.). We, as humans, have the great capacity to direct our visual attention and judge the interestingness of a scene. Consider for example the image sequence in the figure on the right. The spider in front of the camera or the snow on the lens are examples of events that deviate from the context since they violate the expectations, and therefore are considered interesting. On the other hand, weather changes or a camera shift, do not raise human attention considerably, even though large regions of the image are influenced. In this work we firstly investigate what humans consider as "interesting" in image sequences. Secondly we propose a computer vision algorithm to automatically spot these interesting events. To this end, we integrate multiple cues inspired by cognitive concepts and discuss why and to what extent the automatic discovery of visual interestingness is possible.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), not refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Psychology
Dewey Decimal Classification:150 Psychology
Language:English
Event End Date:25 October 2013
Deposited On:10 Dec 2014 18:18
Last Modified:08 Dec 2017 08:58
Publisher:ACM
Additional Information:© 2014 ACM
Publisher DOI:https://doi.org/10.1145/2502081.2502109

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