When the Crowd Challenges the Lab: Lessons Learnt from Subjective Studies on Image Aesthetic Appeal

Crowdsourcing gives researchers the opportunity to collect subjective data quickly, in the real-world, and from a very diverse pool of users. In a long-term study on image aesthetic appeal, we challenged the crowdsourced assessments with typical lab methodologies in order to identify and analyze the impact of crowdsourcing environment on the reliability of subjective data. We identified and conducted three types of crowdsourcing experiments that helped us perform an in-depth analysis of factors influencing reliability and reproducibility of results in uncontrolled crowdsourcing environments. We provide a generalized summary of lessons learnt for future research studies which will try to port lab-based evaluation methodologies into crowdsourcing, so that they can avoid the typical pitfalls in design and analysis of crowdsourcing experiments.

[1]  Huib de Ridder,et al.  Cognitive issues in image quality measurement , 2001, J. Electronic Imaging.

[2]  Aniket Kittur,et al.  Crowdsourcing user studies with Mechanical Turk , 2008, CHI.

[3]  Judith Redi,et al.  Beauty is in the scale of the beholder: Comparison of methodologies for the subjective assessment of image aesthetic appeal , 2014, 2014 Sixth International Workshop on Quality of Multimedia Experience (QoMEX).

[4]  Phuoc Tran-Gia,et al.  Best Practices for QoE Crowdtesting: QoE Assessment With Crowdsourcing , 2014, IEEE Transactions on Multimedia.

[5]  Marcus Barkowsky,et al.  Aligning subjective tests using a low cost common set , 2011 .

[6]  Christian Keimel,et al.  QualityCrowd — A framework for crowd-based quality evaluation , 2012, 2012 Picture Coding Symposium.

[7]  Peter G. Engeldrum,et al.  Psychometric Scaling: A Toolkit for Imaging Systems Development , 2000 .

[8]  Judith Redi,et al.  The role of visual attention in the aesthetic appeal of consumer images: A preliminary study , 2013, 2013 Visual Communications and Image Processing (VCIP).

[9]  Chin-Laung Lei,et al.  A crowdsourceable QoE evaluation framework for multimedia content , 2009, ACM Multimedia.

[10]  Chin-Laung Lei,et al.  Quadrant of euphoria: a crowdsourcing platform for QoE assessment , 2010, IEEE Network.

[11]  Sugato Chakravarty,et al.  Methodology for the subjective assessment of the quality of television pictures , 1995 .

[12]  Jianxiong Xiao,et al.  What makes an image memorable , 2011 .

[13]  Christian Keimel,et al.  Crowdsourcing in QoE Evaluation , 2014, Quality of Experience.

[14]  Jiebo Luo,et al.  Aesthetics and Emotions in Images , 2011, IEEE Signal Processing Magazine.

[15]  Peter Schelkens,et al.  Qualinet White Paper on Definitions of Quality of Experience , 2013 .

[16]  Alon Y. Halevy,et al.  Crowdsourcing systems on the World-Wide Web , 2011, Commun. ACM.

[17]  Judith Redi,et al.  How passive image viewers became active multimedia users : new trends and recent advances in subjective assessment of quality of experience , 2015 .

[18]  Touradj Ebrahimi,et al.  Implicit experiences as a determinant of perceptual quality and aesthetic appreciation , 2011, ACM Multimedia.

[19]  Lew B. Stelmach,et al.  All subjective scales are not created equal: The effects of context on different scales , 1999, Signal Process..

[20]  Pavel Korshunov,et al.  Crowdsourcing-based multimedia subjective evaluations: a case study on image recognizability and aesthetic appeal , 2013, CrowdMM '13.