Collecting and Analyzing Eye-Tracking Data in Outdoor Environments

Natural outdoor conditions pose unique obstacles for researchers, above and beyond those inherent to all mobile eye-tracking research. During analyses of a large set of eye-tracking data collected on geologists examining outdoor scenes, we have found that the nature of calibration, pupil identification, fixation detection, and gaze analysis all require procedures different from those typically used for indoor studies. Here, we discuss each of these challenges and present solutions, which together define a general method useful for investigations relying on outdoor eye-tracking data. We also discuss recommendations for improving the tools that are available, to further increase the accuracy and utility of outdoor eye-tracking data.

[1]  D. Raab Backward masking. , 1963, Psychological bulletin.

[2]  E. Matin Saccadic suppression: a review and an analysis. , 1974, Psychological bulletin.

[3]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[4]  C. Nodine,et al.  Using eye movements to study visual search and to improve tumor detection. , 1987, Radiographics : a review publication of the Radiological Society of North America, Inc.

[5]  David N. Lee,et al.  Where we look when we steer , 1994, Nature.

[6]  D. E. Irwin,et al.  Cognitive Suppression During Saccadic Eye Movements , 1996 .

[7]  M. Land,et al.  The Roles of Vision and Eye Movements in the Control of Activities of Daily Living , 1998, Perception.

[8]  Michael F. Land,et al.  From eye movements to actions: how batsmen hit the ball , 2000, Nature Neuroscience.

[9]  Joseph H. Goldberg,et al.  Identifying fixations and saccades in eye-tracking protocols , 2000, ETRA.

[10]  N. Charness,et al.  The perceptual aspect of skilled performance in chess: Evidence from eye movements , 2001, Memory & cognition.

[11]  Jeff B. Pelz,et al.  Building a lightweight eyetracking headgear , 2004, ETRA.

[12]  D. Ballard,et al.  Eye movements in natural behavior , 2005, Trends in Cognitive Sciences.

[13]  Hugh F. Durrant-Whyte,et al.  Simultaneous localization and mapping: part I , 2006, IEEE Robotics & Automation Magazine.

[14]  Luc Van Gool,et al.  SURF: Speeded Up Robust Features , 2006, ECCV.

[15]  M. Land Eye movements and the control of actions in everyday life , 2006, Progress in Retinal and Eye Research.

[16]  E. Krupinski,et al.  Eye-movement study and human performance using telepathology virtual slides: implications for medical education and differences with experience. , 2006, Human pathology.

[17]  Laura Chamberlain Eye Tracking Methodology; Theory and Practice , 2007 .

[18]  Feng Li,et al.  A model-based approach to video-based eye tracking , 2008 .

[19]  B. Tatler,et al.  Looking and Acting: Vision and eye movements in natural behaviour , 2009 .

[20]  Harry J. Wyatt,et al.  The human pupil and the use of video-based eyetrackers , 2010, Vision Research.

[21]  Toon Goedemé,et al.  Towards a more effective method for analyzing mobile eye-tracking data: integrating gaze data with object recognition algorithms , 2011, PETMEI '11.

[22]  Mahmood Fathy,et al.  Efficient key frames selection for panorama generation from video , 2011, J. Electronic Imaging.

[23]  Matthijs C. Dorst Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[24]  Kenneth Holmqvist,et al.  Eye tracking: a comprehensive guide to methods and measures , 2011 .

[25]  Karen M. Evans,et al.  Analyzing complex gaze behavior in the natural world , 2011, Electronic Imaging.

[26]  Andrew T. Duchowski,et al.  On the conspicuity of 3-D fiducial markers in 2-D projected environments , 2012, ETRA.

[27]  Juan J. Cerrolaza,et al.  Error characterization and compensation in eye tracking systems , 2012, ETRA '12.

[28]  Karen M. Evans,et al.  Ego-motion compensation improves fixation detection in wearable eye tracking , 2012, ETRA.