Paper Info
Title
Predicting Eyes' Fixations in Movie Videos: Visual Saliency Experiments on a New Eye-Tracking Database.
Abstract
In this paper we describe the newly created eye tracking annotated database Eye-Tracking Movie Database ETMD and give some preliminary experimental results on this dataset using our new visual saliency frontend. We have developed a database with eye-tracking human annotation that comprises video clips from Hollywood movies, which are longer in duration than the existing databases' videos and include more complex semantics. Our proposed visual saliency frontend is based on both low-level features, such as intensity, color and spatio-temporal energy, and face detection results and provides a single saliency volume map. The described new eye-tracking database can become useful in many applications while our computational frontend shows to be promising as it gave good results on predicting the eye's fixation according to certain metrics.
Year
DOI
Venue
2014
10.1007/978-3-319-07515-0_19
Lecture Notes in Computer Science
Keywords
Field
DocType
Eye-tracking Database,Visual Saliency,Spatio-Temporal Visual Frontend,3D Gabor Filters,Lab Color Space
Computer vision,Annotation,Fixation (psychology),Salience (neuroscience),Computer science,Eye tracking,Artificial intelligence,Face detection,Database,Semantics,Visual saliency,Lab color space
Conference
Volume
ISSN
Citations 
8532
0302-9743
0
PageRank 
References 
Authors
0.34
7
3
Name
Order
Citations
PageRank
Petros Koutras1166.35
Athanasios Katsamanis230122.71
Petros Maragos33733591.97