Crowdsourcing subjective fashion advice using VizWiz: challenges and opportunities

By Michele A. Burton, Erin L. Brady, Robin N. Brewer, Callie Neylan, Jeffrey P. Bigham, A. Hurst. 2012

103 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Computer Science Applications, Information Systems, Human-Computer Interaction

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Citations in the corpus

VizWiz Grand Challenge: Answering Visual Questions from Blind People (2018, background): “Success in developing automated methods would mitigate concerns about the many undesired consequences from today’s status quo for blind people of relying on humans to answer visual questions [8, 11, 24]; e.”
Mobile Health Applications for the Most Prevalent Conditions by the World Health Organization: Review and Analysis (2013, methodology): “The authors use VizWiz [84] for assisting people with vision impairments in matching garments and being dressed in a fashion way, with the advice of some volunteers Crowdsourcing subjective fashion advice using VizWiz: Challenges and opportunities [83] Low vision”
An Assisted Photography Framework to Help Visually Impaired Users Properly Aim a Camera (2014, background): “Some would also like to use cameras to obtain visual information, like the denomination of currency [Liu 2008] or whether their clothes match [Burton et al. 2012].”
"Person, Shoes, Tree. Is the Person Naked?" What People with Vision Impairments Want in Image Descriptions (2020, methodology): “We identified these sources based on prior work that indicated that people who are BLV want image descriptions to pursue their interests through staying up to date with the news [29], enjoying entertainment media [29], eCommerce [35], staying socially connected [39, 29, 2, 44, 10], dating [31] and p”
Revolt: Collaborative Crowdsourcing for Labeling Machine Learning Datasets (2017, methodology): “Real-time crowdsourcing has been employed for a variety of purposes including minimizing reaction time in crowd-powered user interfaces [7, 6, 9, 34, 36], increasing the speed of data collection [35, 31], and improving data quality by incorporating expert interventions to guide novice workers [11,…”
Understanding Blind People's Experiences with Computer-Generated Captions of Social Media Images (2017, background): “Automatic captioning tools have the potential to empower BVIPs to know more about these images without having to rely on human-authored alt text (which is often missing [4,13,26]) or asking a sighted person (which can be time consuming or burdensome [3,5,6]).”