Abstract


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Click to download BibTeX data Clik to view abstract T. N. Mundhenk, W. Einhaeuser, L. Itti, Natural Image RSVP task performance is predicted by measurements of bottom-up Bayesian Surprise exhibited by image sequences, In: Proc. Vision Science Society Annual Meeting (VSS08), May 2008.

Abstract: The performance of observers on a Rapid Serial Vision Protocol (RSVP) task is causally linked with the amount of bottom-up Bayesian Surprise (buBS) exhibited by both target and distracter images in RSVP sequences. In this paradigm, observers watched a sequence of 20 images at 20Hz. One of the images in the sequence might contain a picture of an animal target at chance. Subjects had to respond as to whether or not they spotted the target. Observers' performance was compared with the amount of buBS images in the sequence exhibited. The buBS information metric defined by (Itti and Baldi 2005; Itti and Baldi 2006) gives a measure of the amount of information gain both within an image (between image locations) and between images. Using the coarse statistics of buBS we were able to alter the performance of observers on an RSVP task by changing the order of images within a sequence. Placing images of high surprise both before and after the target image impairs the ability of observers to recall the target(Einhaeuser, Mundhenk et al. 2007). Here we show coarse statistics for buBS in both color and Gabor orientations is significantly different between RSVP sequences observers find easy (subjects tend to spot the target correctly) compared with ones that observers find difficult. In particular, course statistics for mean buBS are elevated in the flanking images before and after the target in difficult RSVP sequences. Further, buBS is significantly different in some features such as vertical lines as much as 250ms before the target image with a relaxed period 100ms before the target. This lends support to the two stage model of visual processing (Chun and Potter 1995). Additionally, we can use the buBS statistics to inform us of the amount of bottom-up attention capture intrinsic in images in RSVP sequences.

Themes: Model of Bottom-Up Saliency-Based Visual Attention, Scene Understanding

 

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