Consumer-photo quality assessment: Challenges and pitfalls in crowdsourcing

Michele A. Saad, Patrick McKnight, Jake Quartuccio, David G. Nicholas, Ramesh Jaladi, P. Corriveau
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Abstract

We discuss caveats and challenges in crowdsourcing subjective image quality evaluation studies that use real consumer photos with non-simulated distortions. The subtle nature of consumer image artifacts as well as the nuanced quality differences among photos from various consumer devices, necessitate that crowdsourcing studies be designed with extra caution. In this work, we point out certain caveats to look for in the literature, and we draw attention to and discuss the consequences of various design choices on the subjective responses received. The design choices include: 1) stimulus viewing mode, 2) stimulus habituation, 3) study length, and 4) the location of a number of attention items within the study. We show how these design parameters are key to maximizing response correspondence with lab-based responses, and we emphasize to how this differs from tests that utilize simulated image distortions.
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消费者照片质量评估:众包的挑战和陷阱
我们讨论了众包主观图像质量评估研究的警告和挑战,这些研究使用真实的消费者照片和非模拟失真。消费者图像人工制品的微妙性质,以及来自不同消费设备的照片之间细微的质量差异,使得众包研究的设计格外谨慎。在这项工作中,我们指出了在文献中寻找的某些警告,我们提请注意并讨论了各种设计选择对所收到的主观反应的后果。设计选择包括:1)刺激观看模式,2)刺激习惯化,3)研究时长,以及4)研究中若干注意项目的位置。我们展示了这些设计参数是如何与基于实验室的响应最大化响应对应的关键,我们强调了这与利用模拟图像失真的测试的不同之处。
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