@inproceedings {24541,
	title = {Heimdallr: a dataset for sport analysis},
	journal = {ACM Multimedia System},
	year = {2016},
	month = {05/2016},
	publisher = {ACM},
	abstract = {In this paper, we present Heimdallr, a dataset that aims to serve two different purposes. The first purpose is action recognition and pose estimation, which requires a dataset of annotated sequences of athlete skeletons. We employed a crowdsourcing platform where people around the world were asked to annotate frames and obtained more than 3000 fully annotated frames for 42 different sequences with a variety of poses and actions. The second purpose is an improved understanding of crowdworkers, and for this purpose, we collected over 10000 written feedbacks from 592 crowdworkers. This is valuable information for crowdsourcing researchers who explore algorithms for worker quality assessment. In addition to the complete dataset, we also provide the code for the application that has been used to collect the data as an open source software.},
	doi = {http://dl.acm.org/citation.cfm?doid=2910017.2910621},
	author = {Riegler, Michael and Dang-Nguyen, Duc-Tien and Winther, B{\r a}rd and Griwodz, Carsten and Pogorelov, Konstantin and Halvorsen, P{\r a}l}
}
@inproceedings {23566,
	title = {Why Design Matters - Crowdsourcing of Complex Tasks},
	journal = {ACM CrowdMM},
	year = {2015},
	month = {10/2015},
	publisher = {ACM},
	address = {Brisbane, Australia},
	abstract = {In this paper, we show how the power of the crowd can be usedto do complex tasks using human pose estimation as a use case.Crowdsourcing tasks are usually not very complex and easy tosolve by workers that are not experienced in a certain topic. Formore complex tasks, it is general recommended to use experiencedworkers or experts. However, we show that tasks can also be morecomplex for non-expert workers and that they produce data that isclose to what experts would report. Therefore, a detailed descriptionof the crowdsourcing campaign, the methods applied and theresults will be given, and we discuss how the obtained data can beused.},
	keywords = {Annotation, Crowdsourcing, Multimedia},
	doi = {http://dx.doi.org/10.1145/2810188.2810190},
	author = {Winther, B{\r a}rd and Riegler, Michael and Griwodz, Carsten and Halvorsen, P{\r a}l},
	editor = {Calvet, Lilian}
}
