Nonlinear time series analysis
Nonlinear time series analysis
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Experiencing SAX: a novel symbolic representation of time series
Data Mining and Knowledge Discovery
Visual data mining of multimedia data for social and behavioral studies
Information Visualization
Intelligent Data Analysis in the 21st Century
IDA '09 Proceedings of the 8th International Symposium on Intelligent Data Analysis: Advances in Intelligent Data Analysis VIII
Investigating multimodal real-time patterns of joint attention in an hri word learning task
Proceedings of the 5th ACM/IEEE international conference on Human-robot interaction
Active Information Selection: Visual Attention Through the Hands
IEEE Transactions on Autonomous Mental Development
Adaptive eye gaze patterns in interactions with human and artificial agents
ACM Transactions on Interactive Intelligent Systems (TiiS)
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Data-driven knowledge discovery is becoming a new trend in various scientific fields. In light of this, the goal of the present paper is to introduce a novel framework to study one interesting topic in cognitive and behavioral studies – multimodal communication between human-human and human-robot interaction. We present an overall solution from data capture, through data coding and validation, to data analysis and visualization. In data collection, we have developed a multimodal sensing system to gather fine-grained video, audio and human body movement data. In data analysis, we propose a hybrid solution based on visual data mining and information-theoretic measures. We suggest that this data-driven paradigm will lead not only to breakthroughs in understanding multimodal communication, but will also serve as a successful case study to demonstrate the promise of data-intensive discovery which can be applied in various research topics in cognitive and behavioral studies.