some benchmark eye movement datasets ( from State-of-the-Art in Visual Attention Modeling)

1. Some benchmark eye movement datasets over still images often used to evaluate visual attention models.


2009
Kienzle

165
Center-Surround Patterns Emerge as Optimal Predictors for Human Saccade Targets

2008
Einhauser

84
Objects Predict Fixations Better Than Early Saliency

2003
Ouerhani

210
Empirical Validation of Saliency-Based Model of Visual Attention

2005
Bruce and Tsotsos

144
Saliency Based on Information Maximization

www-sop.inria.fr/members/Neil.Bruce

1996
Stark and Choi

211
Experimental Metaphysics: The Scanpath as an Epistemological Mechanism

2010
Chikkerur

154
What and Where: A Bayesian Inference Theory of Visual Attention

www.sharat.org

2003
Torralba

92
Modeling Global Scene Factors in Attention

People.csail.mit.edu/torralba/GlobalFeaturesAndAttention

2009
Judd

166
Learning to Predict Where Humans Look

People.csail.mit.edu/tjudd/WherePeopleLook/index.html

2007
Cerf

167
Predicting Human Gaze Using Low-Level Saliency Combined with Face Detection

www.fifadb.com

2005
Peters

134
Components of Bottom-Up Gaze Allocation in Natural Images

Ilab.usc.edu

1999
Reinagel and Zador

212
Natural Scenes at the Center of Gaze

Zadorlab.cshl.edu

2008
Hwang and Pomplun

86
A Model of Top-Down Control of Attention during Visual Search in Real-World Scenes

www.cs.umb.edu/~marc

2008
Kootstra

136
Paying Attention to Symmetry

www.csc.kth.se/~kootstra

2007
Tatler

123
The Central Fixation Bias in Scene Viewing: Selecting an Optimal Viewing Position Independently of Motor Bases and Image Feature Distributions

www.activevisionlab.org

2009
Engmann

182
Saliency on a Natural Scene Background: Effects of Color and Luminance Contrast Add Linearly

2009
Engelke

213
Visual Attention Modeling: Region-of-Interest Versus Fixation Patterns

2006
Le Meur

41
A Coherent Computational Approach to Model Bottom-Up Visual Attention

www.irisa.fr/temics/staff/lemeur

2009
Ehinger

87
Modeling Search for People in 900 Scenes: A Combined Source Model of Eye Guidance

Cvcl.mit.edu/searchmodels/

2008
Rajashekar

174
GAFFE: A Gaze-Attentive Fixation Finding Engine

Live.ece.utexas.edu/research/doves/

2. Some benchmark eye movement datasets over video stimuli for evaluating visual attention prediction


2005
CRCNS-ORIG

145
Bayesian Surprise Attracts Human Attention

Crcns.org/data-sets/eye/eye-1

2005
CRCNS-MTV

145
Bayesian Surprise Attracts Human Attention

Crcns.org/data-sets/eye/eye-1

2010
Jia li

133
Probabilistic Multi-Task Learning for Visual Saliency Estimation in Video

www.jdl.ac.cn/user/jiali/

2007
Peters and Itti

101
Beyond Bottom-up: Incorporating Taskdependent

Influences into a Computational Model of Spatial Attention

Ilab.usc.edu/rjpeters/

2007
Shic and Scassellati

74
A Behavioral Analysis of Computational Models of Visual Attention

Sites.google.com/site/fredshic/home

2007
Marat

49
Video Summarization Using a Visual Attention Model

Star1g.ovh.net/~qgsmabaq/sophie/index.php

2007
Le Meur

138
Predicting Visual Fixations on Video Based on Low-Level Visual Features

www.irisa.fr/temics/staff/lemeur
时间： 2024-11-11 10:15:10

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