Efficiently scaling up video annotation with crowdsourced marketplaces
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Human computation: a survey and taxonomy of a growing field
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Video summarization via crowdsourcing
CHI '11 Extended Abstracts on Human Factors in Computing Systems
A survey of semantic image and video annotation tools
Knowledge-driven multimedia information extraction and ontology evolution
Guess what? a game for affective annotation of video using crowd sourcing
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part I
Designing persuasive robots: how robots might persuade people using vocal and nonverbal cues
HRI '12 Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction
Towards building a virtual counselor: modeling nonverbal behavior during intimate self-disclosure
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Proceedings of the 14th ACM international conference on Multimodal interaction
Crowdsourcing micro-level multimedia annotations: the challenges of evaluation and interface
Proceedings of the ACM multimedia 2012 workshop on Crowdsourcing for multimedia
Proceedings of the 15th ACM on International conference on multimodal interaction
Mutual Behaviors during Dyadic Negotiation: Automatic Prediction of Respondent Reactions
ACII '13 Proceedings of the 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction
| Hi-index | 0.00 |
With an exponential growth in social multimedia contents online, there is an increasing importance of understanding why and how some contents are perceived as persuasive while others are ignored. This paper outlines my research goals in understanding human perception of persuasiveness in social multimedia contents, which involve studying how different communication modalities influence our perception and identifying key verbal and nonverbal behaviors that eventually lead us to believe someone is convincing and influential. For any research involving in-depth human behavior analysis, it is imperative to obtain accurate annotations of human behaviors at the micro-level. In addition to investigating persuasiveness, this work will also provide to the research community convenient web-based annotation tools, effective procedures for obtaining high-quality annotations with crowdsourcing, and evaluation metrics to fairly and accurately measure the quality and agreement of micro-level behavior annotations.