Algorithms for Defining Visual Regions-of-Interest: Comparison with Eye Fixations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational Statistics Handbook with MATLAB, Second Edition (Chapman & Hall/Crc Computer Science & Data Analysis)
A Comparison of Feature Detectors with Passive and Task-Based Visual Saliency
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Extraction of visual features with eye tracking for saliency driven 2D/3D registration
Image and Vision Computing
Towards automatic polyp detection with a polyp appearance model
Pattern Recognition
Learning-Based Prediction of Visual Attention for Video Signals
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
We present in this paper a novel study aiming at identifying the differences in visual search patterns between physicians of diverse levels of expertise during the screening of colonoscopy videos. Physicians were clustered into two groups -experts and novices- according to the number of procedures performed, and fixations were captured by an eye-tracker device during the task of polyp search in different video sequences. These fixations were integrated into heat maps, one for each cluster. The obtained maps were validated over a ground truth consisting of a mask of the polyp, and the comparison between experts and novices was performed by using metrics such as reaction time, dwelling time and energy concentration ratio. Experimental results show a statistically significant difference between experts and novices, and the obtained maps show to be a useful tool for the characterisation of the behaviour of each group.