Observing Pictures and Videos of Creative Products: An Eye Tracking Study

[1]  Hong Wang,et al.  Automobile Modeling Evaluations Based on Electrophysiology , 2010 .

[2]  K. V. Beurden,et al.  EMOGRAM: HELP (STUDENT) DESIGN RESEARCHERS UNDERSTANDING USER EMOTIONS IN PRODUCT DESIGN , 2019, DS 95: Proceedings of the 21st International Conference on Engineering and Product Design Education (E&PDE 2019), University of Strathclyde, Glasgow. 12th -13th September 2019.

[3]  Ali Akgunduz,et al.  Pair-Wise Preference Comparisons Using Alpha-Peak Frequencies , 2012, J. Integr. Des. Process. Sci..

[4]  Pierre-Antoine Arrighi,et al.  Towards Co-designing with Users: A Mixed Reality Tool for Kansei Engineering , 2015, PLM.

[5]  Manuel Contero,et al.  Using Combined Bipolar Semantic Scales and Eye‐Tracking Metrics to Compare Consumer Perception of Real and Virtual Bottles , 2015 .

[6]  Carole Bouchard,et al.  Emotion finds a way to users from designers: assessing product images to convey designer's emotion , 2012 .

[7]  Francisco Muñoz-Leiva,et al.  What type of online advertising is most effective for eTourism 2.0? An eye tracking study based on the characteristics of tourists , 2015, Comput. Hum. Behav..

[8]  Chun-Heng Ho,et al.  Can pupil size be measured to assess design products , 2014 .

[9]  Federico Rotini,et al.  Product Planning techniques: investigating the differences between research trajectories and industry expectations , 2016 .

[10]  Erkan Gunpinar,et al.  Eye tracking for screening design parameters in adjective-based design of yacht hull , 2018, Ocean Engineering.

[11]  Graham Green,et al.  Quantifying the qualities of aesthetics in product design using eye-tracking technology , 2015 .

[12]  Ariel Telpaz,et al.  Using EEG to Predict Consumers’ Future Choices , 2015 .

[13]  José E. Lugo,et al.  Part-Worth Utilities of Gestalt Principles for Product Esthetics: A Case Study of a Bottle Silhouette , 2016 .

[14]  Amalia Suzianti,et al.  AN ANALYSIS OF COGNITIVE˗BASED DESIGN OF YOGURT PRODUCT PACKAGING , 2015 .

[15]  M. Montero Perez Pre-learning vocabulary before viewing captioned video: an eye-tracking study , 2019, The Language Learning Journal.

[16]  José Gaspar,et al.  User satisfaction modeling framework for automotive audio interfaces , 2014 .

[17]  Juyeon Park,et al.  Exploring product communication between the designer and the user through eye-tracking technology , 2012 .

[18]  Manuel Contero,et al.  Design Perception: Combining Semantic Priming With Eye Tracking and Event-Related Potential (ERP) Techniques to Identify Salient Product Visual Attributes , 2015 .

[19]  Demis Basso,et al.  Value Perception of Green Products: An Exploratory Study Combining Conscious Answers and Unconscious Behavioral Aspects , 2019, Sustainability.

[20]  Bülent Yilmaz,et al.  Like/dislike analysis using EEG: Determination of most discriminative channels and frequencies , 2014, Comput. Methods Programs Biomed..

[21]  Jeffrey Hartley,et al.  Evaluations That Matter: Customer Preferences Using Industry-Based Evaluations and Eye-Gaze Data , 2016 .

[22]  Monica Bordegoni,et al.  A Method for Designing Users’ Experience with Industrial Products based on a Multimodal Environment and Mixed Prototypes , 2013 .

[23]  Wenrong Liu,et al.  Research on UX evaluation method of design concept under multi-modal experience scenario in the earlier design stages , 2018 .

[24]  José E. Lugo,et al.  An immersive virtual discrete choice experiment for elicitation of product aesthetics using Gestalt principles , 2017, Design Science.

[25]  Yukari Nagai,et al.  A Study on Product Display Using Eye-Tracking Systems , 2017 .

[26]  James Self,et al.  Mode-of-use Innovation in Interactive Product Development , 2017 .

[27]  Erin F. MacDonald,et al.  A Test of the Rapid Formation of Design Cues for Product Body Shapes and Features , 2018 .

[28]  Yi Zhu,et al.  Research on User’s Perceptual Preference of Automobile Styling , 2018 .

[29]  Siti Mastura Ishak,et al.  ASSESSING EYE FIXATION BEHAVIOUR THROUGH DESIGN EVALUATION OF LAWI AYAM ARTEFACT , 2015 .

[30]  Minjeong Kim Digital product presentation, information processing, need for cognition and behavioral intent in digital commerce , 2019, Journal of Retailing and Consumer Services.

[31]  Yuri Borgianni,et al.  Review of the use of neurophysiological and biometric measures in experimental design research , 2020, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[32]  Erin F. MacDonald,et al.  Products' Shared Visual Features Do Not Cancel in Consumer Decisions , 2015 .

[33]  Carole Bouchard,et al.  Evaluating Perceived Quality through Sensory Evaluation in the Development Process of New Products: A Case Study of Luxury Market , 2018 .

[34]  Fei-Hui Huang,et al.  Understanding user acceptance of battery swapping service of sustainable transport: An empirical study of a battery swap station for electric scooters, Taiwan , 2020, International Journal of Sustainable Transportation.

[35]  Xian Yang,et al.  User intent perception by gesture and eye tracking , 2016 .

[36]  Janni Nielsen,et al.  The eye of the user: the influence of movement on users' visual attention , 2002, Digit. Creativity.

[37]  A. M. R. Ribeiro,et al.  Psychoacoustics of in-car switch buttons: From feelings to engineering parameters , 2016 .

[38]  Johann Gamper,et al.  Visual time period analysis: a multimedia analytics application for summarizing and analyzing eye-tracking experiments , 2019, Multimedia Tools and Applications.

[39]  Puneet Tandon,et al.  Product design concept evaluation using rough sets and VIKOR method , 2016, Adv. Eng. Informatics.

[40]  Michael C. Frank,et al.  Vision-Based Classification of Developmental Disorders Using Eye-Movements , 2016, MICCAI.

[41]  Jonathan Cagan,et al.  Understanding Consumer Tradeoffs Between Form and Function Through Metaconjoint and Cognitive Neuroscience Analyses , 2013 .

[42]  Sascha Mahlke,et al.  Evaluation of Six Night Vision Enhancement Systems: Qualitative and Quantitative Support for Intelligent Image Processing , 2007, Hum. Factors.

[43]  Sarah Diefenbach,et al.  The impact of concept (re)presentation on users' evaluation and perception , 2010, NordiCHI.

[44]  Robert Schmitt,et al.  Applying Eye-Tracking in Kansei Engineering Method for Design Evaluations in Product Development , 2014 .

[45]  Hasan Ayaz,et al.  Eye Tracking-Based Workload and Performance Assessment for Skill Acquisition , 2019, AHFE.

[46]  Michael Bourlakis,et al.  Virtual test-driving: The impact of simulated products on purchase intention , 2014 .

[47]  Ji-Hyun Lee,et al.  The gap between design intent and user response: identifying typical and novel car design elements among car brands for evaluating visual significance , 2017, J. Intell. Manuf..

[48]  Erin F. MacDonald,et al.  Eye-Tracking Data Predict Importance of Product Features and Saliency of Size Change , 2014 .

[49]  Anders Gustafsson,et al.  Design and evaluation of a personalisable user interface in a vehicle context , 2014 .

[50]  Federico Rotini,et al.  Investigating the future of the fuzzy front end: towards a change of paradigm in the very early design phases? , 2018, Journal of Engineering Design.

[51]  Zhangyu Ji,et al.  Research on the Effect of Mechanical Drawings’ Different Marked Way on Browse and Search Efficiency Based on Eye-Tracking Technology , 2017 .

[52]  Mirko Meboldt,et al.  Automated interpretation of eye–hand coordination in mobile eye tracking recordings , 2017, KI - Künstliche Intelligenz.

[53]  Andy Dong,et al.  Eye Gaze Experiment Into the Recognition of Intended Affordances , 2017 .

[54]  Stefano Tornincasa,et al.  3D Facial Action Units and Expression Recognition using a Crisp Logic , 2018, Computer-Aided Design and Applications.

[55]  Carole Bouchard,et al.  Interdependency between user experience and interaction: a Kansei design approach , 2018 .

[56]  Mo Chen,et al.  Interpreting and tailoring affordance based design user-centered experiments , 2020, International Journal of Design Creativity and Innovation.

[57]  D. Basso,et al.  Exploratory study on the perception of additively manufactured end-use products with specific questionnaires and eye-tracking , 2019, International Journal on Interactive Design and Manufacturing (IJIDeM).

[58]  Halszka Jarodzka,et al.  Before your very eyes: the value and limitations of eye tracking in medical education , 2017, Medical education.

[59]  Sarah Diefenbach,et al.  Idealization Effects in UX Evaluation at Early Concept Stages: Challenges of Low-Fidelity Prototyping , 2018 .

[60]  Shih-Wen Hsiao,et al.  An online affordance evaluation model for product design , 2012 .

[61]  Klementina Možina,et al.  Do prominent warnings make packaging less attractive? , 2018, Safety Science.

[62]  C. Chen,et al.  The effect of product characteristic familiarity on product recognition , 2017 .

[63]  Zhan Gao,et al.  A comparative study of virtual prototyping and physical prototyping , 2004, Int. J. Manuf. Technol. Manag..

[64]  Semiha Ergan,et al.  Quantifying Human Experience in Architectural Spaces with Integrated Virtual Reality and Body Sensor Networks , 2019, Journal of Computing in Civil Engineering.

[65]  Christian Nøhr,et al.  Participatory Design, User Involvement and Health IT Evaluation. , 2016, Studies in health technology and informatics.

[66]  Yi Ding,et al.  Can eye-tracking data be measured to assess product design?: Visual attention mechanism should be considered , 2016 .

[67]  Jinjuan She,et al.  Exploring the Effects of a Product's Sustainability Triggers on Pro-Environmental Decision-Making , 2018 .

[68]  Fabiola H. Gerpott,et al.  In the eye of the beholder? An eye-tracking experiment on emergent leadership in team interactions , 2017 .

[69]  Vishal Sethi,et al.  An intelligent recommendation system using gaze and emotion detection , 2018, Multimedia Tools and Applications.

[70]  Long Wang,et al.  A model based on eye movement data and artificial neutral network for product styling evaluation , 2018, 2018 24th International Conference on Automation and Computing (ICAC).

[71]  Yixiong Feng,et al.  A Cyber-Physical System for Product Conceptual Design Based on an Intelligent Psycho-Physiological Approach , 2017, IEEE Access.

[72]  T. Foulsham,et al.  Comparing scanpaths during scene encoding and recognition : A multi-dimensional approach , 2012 .

[73]  Michele Germani,et al.  Virtual vs. Physical: An Experimental Study to Improve Shape Perception , 2009 .

[74]  Jordan J. Louviere,et al.  Consumer neuroscience: Assessing the brain response to marketing stimuli using electroencephalogram (EEG) and eye tracking , 2013, Expert Syst. Appl..

[75]  Francesca Nonis,et al.  3D Approaches and Challenges in Facial Expression Recognition Algorithms—A Literature Review , 2019, Applied Sciences.

[76]  Rupert Andrew Hurley,et al.  The Effect of Modifying Structure to Display Product Versus Graphical Representation on Packaging , 2013 .

[77]  John Payne,et al.  AutoEval mkII - Interaction Design for a VR Design Review System , 2007, 2007 IEEE Symposium on 3D User Interfaces.

[78]  S. Tsai,et al.  Empirical research on Kano’s model and customer satisfaction , 2017, PloS one.

[79]  Veena Chattaraman,et al.  Creating an Affective Design Typology for Basketball Shoes Using Kansei Engineering Methods , 2018, Advances in Intelligent Systems and Computing.

[80]  Robert Schmitt,et al.  Objectifying user attention and emotion evoked by relevant perceived product components , 2014 .

[81]  Ming-Chuen Chuang,et al.  Relationship between eye fixation patterns and Kansei evaluation of 3D chair forms , 2017, Displays.

[82]  Beverly E. Faulkner-Jones,et al.  Eye-Tracking in the Study of Visual Expertise: Methodology and Approaches in Medicine , 2017 .

[83]  Yi Wang,et al.  A novel method for the evaluation of fashion product design based on data mining , 2017 .