Examining the effect of task on viewing behavior in videos using saliency maps

Research has shown that when viewing still images, people will look at these images in a different manner if instructed to evaluate their quality. They will tend to focus less on the main features of the image and, instead, scan the entire image area looking for clues for its level of quality. It is questionable, however, whether this finding can be extended to videos considering their dynamic nature. One can argue that when watching a video the viewer will always focus on the dynamically changing features of the video regardless of the given task. To test whether this is true, an experiment was conducted where half of the participants viewed videos with the task of quality evaluation while the other half were simply told to watch the videos as if they were watching a movie on TV or a video downloaded from the internet. The videos contained content which was degraded with compression artifacts over a wide range of quality. An eye tracking device was used to record the viewing behavior in both conditions. By comparing the behavior during each task, it was possible to observe a systematic difference in the viewing behavior which seemed to correlate to the quality of the videos.

[1]  S Ullman,et al.  Shifts in selective visual attention: towards the underlying neural circuitry. , 1985, Human neurobiology.

[2]  M. Tinker How People Look at Pictures. , 1936 .

[3]  Patrick Le Callet,et al.  Overt visual attention for free-viewing and quality assessment tasks Impact of the regions of interest on a video quality metric , 2010 .

[4]  Christof Koch,et al.  A Model of Saliency-Based Visual Attention for Rapid Scene Analysis , 2009 .

[5]  Judith Redi,et al.  Interactions of visual attention and quality perception , 2011, Electronic Imaging.

[6]  Alan C. Bovik,et al.  A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms , 2006, IEEE Transactions on Image Processing.

[7]  Judith Redi,et al.  Image quality and visual attention interactions: Towards a more reliable analysis in the saliency space , 2011, 2011 Third International Workshop on Quality of Multimedia Experience.

[8]  O. Meur,et al.  Predicting visual fixations on video based on low-level visual features , 2007, Vision Research.

[9]  Ingrid Heynderickx,et al.  Visual Attention in Objective Image Quality Assessment: Based on Eye-Tracking Data , 2011, IEEE Transactions on Circuits and Systems for Video Technology.

[10]  A. L. Yarbus,et al.  Eye Movements and Vision , 1967, Springer US.

[11]  Jukka Häkkinen,et al.  Can eye movements be quantitatively applied to image quality studies? , 2004, NordiCHI '04.

[12]  Ingrid Heynderickx,et al.  How the task of evaluating image quality influences viewing behavior , 2011, 2011 Third International Workshop on Quality of Multimedia Experience.

[13]  Sugato Chakravarty,et al.  Methodology for the subjective assessment of the quality of television pictures , 1995 .

[14]  John K. Tsotsos,et al.  Saliency, attention, and visual search: an information theoretic approach. , 2009, Journal of vision.

[15]  A. L. I︠A︡rbus Eye Movements and Vision , 1967 .

[16]  Nancy Millette,et al.  How People Look at Pictures , 1935 .

[17]  Patrick Le Callet,et al.  Task impact on the visual attention in subjective image quality assessment , 2006, 2006 14th European Signal Processing Conference.

[18]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[19]  Touradj Ebrahimi,et al.  The JPEG 2000 still image compression standard , 2001, IEEE Signal Process. Mag..