Generating Annotations for How-to Videos Using Crowdsourcing

Conference on Human Factors in Computing Systems - Proceedings

Volumn 2013-April, Issue , 2013, Pages 835-840

  Nguyen, Phu ^a   Kim, Juho ^a   Miller, Robert C ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Crowd workers; How to videos; Video tutorials

Indexed keywords

CROWDSOURCING; HUMAN ENGINEERING; INDEXING (OF INFORMATION);

AMAZON MECHANICAL TURKS; ANNOTATION TOOL; CROWD WORKERS; HOW-TO VIDEOS; THREE-STAGE METHOD; TIME STAMPS; VIDEO INDEXING; VIDEO TUTORIALS;

HUMAN COMPUTER INTERACTION;

EID: 84983241542     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2468356.2468506     Document Type: Conference Paper

References (5)

1. Bernstein, M., Little, G., Miller, R., et al. Soylent: A Word Processor with a Crowd Inside. UIST ‘10, ACM Press (2010).
2. Kim, J. ToolScape: Enhancing the Learning Experience of How-to Videos. In Proc. of CHI 2013 Extended Abstracts, to appear.
3. Murphy, K. and Freeman W. LabelMe: a database and web-based tool for image annotation. Int. J. Comput. Vision 77, 1-3 (May 2008), 157-173.
4. Sorokin, A. and Forsyth, D. Utility data annotation with Amazon Mechanical Turk. CVPR ‘08, (2008).
5. von Ahn, L. and Dabbish, L. Labeling images with a computer game. CHI ‘04, ACM Press (2004).