Predicting Consumer Choice from Raw Eye-Movement Data Using the RETINA Deep Learning Architecture PDF Download
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Author: Moshe Unger
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Research has revealed the potential of recording consumers' eye movements to characterize and predict their decision making. In this paper, we propose the use of a deep learning architecture, called RETINA, to predict multi-alternative, multi-attribute consumer choice from eye movement data. Unlike previous research, RETINA uses the raw eye-tracking data from both eyes as input. It combines state-of-the art BERT and Metric Learning methods which capitalize on the key characteristics of the raw eye-tracking data. Using the raw data input eliminates the information loss that may result from first calculating fixations, deriving metrics from the fixations data and analysing those metrics, as is usually done in eye movement research. While Deep Learning architectures often require very large data sets, using the raw gaze data allows us to apply Deep Learning to eye tracking data sets of the size commonly encountered in academic and applied research. Using a data set with 112 respondents who made choices among four laptops, we show that the proposed architecture outperforms other state-of-the-art machine learning methods (standard BERT, LSTM, autoML, logistic regression) calibrated on raw data or fixation data. Using autoML, we provide an assessment of which features of the eye movement data contribute to the prediction of consumer choice behavior. The analysis of partial time and partial data segments reveals the ability of RETINA to predict choice outcomes well before a decision has been reached. We provide recommendations on how the proposed deep learning architecture can be used to improve marketing.
Author: Moshe Unger
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Research has revealed the potential of recording consumers' eye movements to characterize and predict their decision making. In this paper, we propose the use of a deep learning architecture, called RETINA, to predict multi-alternative, multi-attribute consumer choice from eye movement data. Unlike previous research, RETINA uses the raw eye-tracking data from both eyes as input. It combines state-of-the art BERT and Metric Learning methods which capitalize on the key characteristics of the raw eye-tracking data. Using the raw data input eliminates the information loss that may result from first calculating fixations, deriving metrics from the fixations data and analysing those metrics, as is usually done in eye movement research. While Deep Learning architectures often require very large data sets, using the raw gaze data allows us to apply Deep Learning to eye tracking data sets of the size commonly encountered in academic and applied research. Using a data set with 112 respondents who made choices among four laptops, we show that the proposed architecture outperforms other state-of-the-art machine learning methods (standard BERT, LSTM, autoML, logistic regression) calibrated on raw data or fixation data. Using autoML, we provide an assessment of which features of the eye movement data contribute to the prediction of consumer choice behavior. The analysis of partial time and partial data segments reveals the ability of RETINA to predict choice outcomes well before a decision has been reached. We provide recommendations on how the proposed deep learning architecture can be used to improve marketing.
Author: Sahar Mahdie Klim Al-Zaidawi
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
The advent of modern eye tracking devices has spawned a plethora of new research on eye movements. Applications of these research results include the prediction of diseases, of biometrics, of gender, or of cognitive developments in children. One par- ticularly well studied topic is user identification. Another, less well studied one is gender prediction. In this thesis, a common framework to predict users and gen- der is proposed. Using this framework, we were able to improve the state-of-the-art accuracies for both user identification and gender prediction. Further, unlike previ- ous studies, the proposed approach was tested with different datasets consisting of varying stimuli. We identify several factors that affect the identification accuracy. Our main improvements in identification accuracy are due to three factors, select- ing optimal hyper-parameters of the segmentation algorithm, adding higher-order derivatives, and including blink information. For gender prediction, the thesis es- tablishes several new insights. For instance, that gender prediction is possible for prepubescent children aged 9-10. Previous research had suggested that significant gender differences in eye movements can only be observed in adults. Various factors are identified which affect the accuracy of gender prediction; for example, the length of the gaze trajectory, possible fatigue of the participant (gender prediction works better in the presence of fatigue), and the choice of feature ranking algorithms.
Author: Mike Horsley
Publisher: Springer Science & Business Media
ISBN: 3319028685
Category : Education
Languages : en
Pages : 340
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Book Description
Our eye movements in response to visual stimuli reveal much about how we experience the world. Focusing on the latest developments in the multidisciplinary field of eye tracking research, this volume ranges across a wide spectrum of research applications, with four sections covering the plethora of practical uses to which our expanding knowledge can be put. They offer abundant evidence that eye tracking research and its methodologies offer new ways of collecting data, framing research questions, and thinking about how we view our world. As a result, we are discovering more about how the visual system works, as well as how it interacts with attention, cognition, and behaviour. Current Trends in Eye Tracking Research presents the work of more than 50 researchers and academics, showcasing groundbreaking studies and innovative ways of applying eye tracking technologies to interesting research problems. The book covers the current output of a number of pioneering research laboratories, detailing their work on eye tracking and the visual system, alignment and EEG data, marketing and social applications, and eye tracking in education. Featuring creative uses of existing technology as well as inventive implementation of new technology in a range of research contexts and disciplines, this new publication is compelling proof of the growing importance of this exciting and fast-moving area of scientific endeavor.
Author: Michael Burch
Publisher: CRC Press
ISBN: 1000792943
Category : Computers
Languages : en
Pages : 380
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Book Description
Visualization and visual analytics are powerful concepts for exploring data from various application domains. The endless number of possible parameters and the many ways to combine visual variables as well as algorithms and interaction techniques create lots of possibilities for building such techniques and tools. The major goal of those tools is to include the human users with their tasks at hand, their hypotheses, and research questions to provide ways to find solutions to their problems or at least to hint them in a certain direction to come closer to a problem solution. However, due to the sheer number of design variations, it is unclear which technique is suitable for those tasks at hand, requiring some kind of user evaluation to figure out how the human users perform while solving their tasks. The technology of eye tracking has existed for a long time; however, it has only recently been applied to visualization and visual analytics as a means to provide insights to the users’ visual attention behavior. This generates another kind of dataset that has a spatio-temporal nature and hence demands for advanced data science and visual analytics concepts to find insights into the recorded eye movement data, either as a post process or even in real-time. This book describes aspects from the interdisciplinary field of visual analytics, but also discusses more general approaches from the field of visualization as well as algorithms and data handling. A major part of the book covers research on those aspects under the light and perspective of eye tracking, building synergy effects between both fields – eye tracking and visual analytics – in both directions, i.e. eye tracking applied to visual analytics and visual analytics applied to eye tracking data. Technical topics discussed in the book include: • Visualization; • Visual Analytics; • User Evaluation; • Eye Tracking; • Eye Tracking Data Analytics; Eye Tracking and Visual Analytics includes more than 500 references from the fields of visualization, visual analytics, user evaluation, eye tracking, and data science, all fields which have their roots in computer science. Eye Tracking and Visual Analytics is written for researchers in both academia and industry, particularly newcomers starting their PhD, but also for PostDocs and professionals with a longer research history in one or more of the covered research fields. Moreover, it can be used to get an overview about one or more of the involved fields and to understand the interface and synergy effects between all of those fields. The book might even be used for teaching lectures in the fields of information visualization, visual analytics, and/or eye tracking.
Author: Andrew T. Duchowski
Publisher: Springer
ISBN: 3319578839
Category : Computers
Languages : en
Pages : 387
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Book Description
This book focuses on video-based, corneal-reflection eye trackers – the most widely available and affordable type of system, and takes a look at a number of interesting and challenging applications in human factors, collaborative systems, virtual reality, marketing and advertising. The third edition has been extensively revised and extended, and includes new chapters on calibration accuracy, precision and correction; advanced eye movement analysis; binocular eye movement analysis; practical gaze analytics; design; GIS. Opening with useful background information, including an introduction to the human visual system and key issues in visual perception and eye movement, the author then surveys eye-tracking devices and provides a detailed introduction to the technical requirements necessary for installing a system and developing an application program.
Author: Zhiguo Wang
Publisher: Springer Nature
ISBN: 303082635X
Category : Psychology
Languages : en
Pages : 237
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Book Description
Several Python programming books feature tools designed for experimental psychologists. What sets this book apart is its focus on eye-tracking. Eye-tracking is a widely used research technique in psychology and neuroscience labs. Research grade eye-trackers are typically faster, more accurate, and of course, more expensive than the ones seen in consumer goods or usability labs. Not surprisingly, a successful eye-tracking study usually requires sophisticated computer programming. Easy syntax and flexibility make Python a perfect choice for this task, especially for psychology researchers with little or no computer programming experience. This book offers detailed coverage of the Pylink library, a Python interface for the gold standard EyeLink ® eye-trackers, with many step-by-step example scripts. This book is a useful reference for eye-tracking researchers, but you can also use it as a textbook for graduate-level programming courses.
Author: Prateek Bansal
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
With the increased affordability of eye-tracking technology, many sub-disciplines of economics have started collecting consumers' eye movements during discrete choice experiments (DCEs). This paper provides a comprehensive understanding of the state-of-the-art visual attention measures, methods to incorporate eye movement data within discrete choice models (DCMs), and novel insights about the correlations among task complexity, visual attention, fatigue and learning during DCE, and preference stability. We argue that the eye-tracking data could not generate a practical value due to four main reasons. First, visual attention does not imply that the respondent has attended to the information. Second, static DCMs are unsuitable to model dynamic process data. Third, most studies have derived descriptive (instead of inferential) behavioural insights, which are not valuable in improving DCE design or DCMs. Fourth, DCMs are calibrated using small non-representative samples, which are not valuable beyond lab-based settings. To improve the practical relevance of eye-tracking research, we propose potential pathways or approaches to (i) use eye-tracking data in designing DCEs to minimise attribute non-attendance while maximising statistical efficiency (i.e., encouraging compensatory decision process), (ii) integrate eye-tracking data with electroencephalogram (EEG) data to distinguish attention and attendance, (iii) jointly model web-based DCE data and lab-based DCE data with eye movement to handle the sample size issue and demonstrate the value of eye-movement data beyond lab-based settings for practical application, (iv) infer non-compensatory decision rules from eye-movement trajectories, and (v) adopt sequential sampling models from cognitive psychology, which provide a principled approach to model neurophysiological data.
Author: Michel Wedel
Publisher: Now Publishers Inc
ISBN: 1601981546
Category : Business & Economics
Languages : en
Pages : 105
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Book Description
Eye-Tracking for Visual Marketing examines the structure of the eye, the visual brain, eye-movements, and methods for recording and analyzing them. It describes the authors' theory and reviews eye-tracking applications in marketing based on this theory.
Author: Kenneth Holmqvist
Publisher: Oxford University Press, USA
ISBN: 9780198738596
Category :
Languages : en
Pages : 560
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Book Description
We make 3-5 eye movements per second, and these movements are crucial in helping us deal with the vast amounts of information we encounter in our everyday lives. In recent years, thanks to the development of eye tracking technology, there has been a growing interest in monitoring and measuring these movements, with a view to understanding how we attend to and process the visual information we encounter. Eye tracking as a research tool is now more accessible than ever, and is growing in popularity amongst researchers from a whole host of different disciplines. Usability analysts, sports scientists, cognitive psychologists, reading researchers, psycholinguists, neurophysiologists, electrical engineers, and others, all have a vested interest in eye tracking for different reasons. The ability to record eye-movements has helped advance our science and led to technological innovations. However, the growth of eye tracking in recent years has also presented a variety of challenges - in particular the issue of how to design an eye-tracking experiment, and how to analyse the data. This book is a much needed comprehensive handbook of eye tracking methodology. It describes how to evaluate and acquire an eye-tracker, how to plan and design an eye tracking study, and how to record and analyse eye-movement data. Besides technical details and theory, the heart of this book revolves around practicality - how raw data samples are converted into fixations and saccades using event detection algorithms, how the different representations of eye movement data are calculated using AOIs, heat maps and scanpaths, and how all the measures of eye movements relate to these processes. Part I presents the technology and skills needed to perform high-quality research with eye-trackers. Part II covers the predominant methods applied to the data which eye-trackers record. These include the parsing of raw sample data into oculomotor events, and how to calculate other representations of eye movements such as heat maps and transition matrices. Part III gives a comprehensive outline of the measures which can be calculated using the events and representations described in Part II. This is a taxonomy of the measures available to eye-tracking researchers, sorted by type of movement of the eyes and type of analysis. For anyone in the sciences considering conducting research involving eye-tracking, this book will be an essential reference work.
Author: Roger PG van Gompel
Publisher: Elsevier
ISBN: 0080474918
Category : Medical
Languages : en
Pages : 755
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Book Description
Eye-movement recording has become the method of choice in a wide variety of disciplines investigating how the mind and brain work. This volume brings together recent, high-quality eye-movement research from many different disciplines and, in doing so, presents a comprehensive overview of the state-of-the-art in eye-movement research. Sections include the history of eye-movement research, physiological and clinical studies of eye movements, transsaccadic integration, computational modelling of eye movements, reading, spoken language processing, attention and scene perception, and eye-movements in natural environments. Includes recent research from a variety of disciplines Divided into sections based on topic areas, with an overview chapter beginning each section Through the study of eye movements we can learn about the human mind, and eye movement recording has become the method of choice in many disciplines
