Can Visual Scanpath Reveal Personal Image Memorability? Investigation of HMM Tools for Gaze Patterns Analysis
Waqas Ellahi, Toinon Vigier, Patrick Le Callet
Abstract
Visual attention has been shown as a good proxy for QoE, revealing specific visual patterns considering content, system and contextual aspects of a multimedia applications. In this paper, we propose a novel approach based on hidden markov models to analyze visual scanpaths in an image memorability task. This new method ensures the consideration of both temporal and idiosyncrasic aspects of visual behavior. The study shows promising results for the use of indirect measures for the personalization of QoE assessment and prediction.
Topics & Concepts
Computer scienceHidden Markov modelPersonalizationGazeVisualizationArtificial intelligenceEye trackingTask (project management)Visual attentionHuman–computer interactionMachine learningPattern recognition (psychology)World Wide WebPerceptionManagementNeuroscienceEconomicsBiologyVisual Attention and Saliency DetectionGaze Tracking and Assistive TechnologyImage and Video Quality Assessment