Cooperation Level Estimation of Pair Work Using Top-view Image

To understand an interaction among persons is one of the most important tasks in artificial intelligence. In this paper, we propose a method for estimating a cooperation level in pair work. The task is a cooperation work that take place in front of a whiteboard by two persons. The goal of our study is to provide the cooperation level that is estimated by features extracted from images for teachers. The result of this study is useful for education support systems and problem based learning. We extract the standing location, operation ratio and head direction of each person from an overhead camera. We apply the features to two machine learning approaches: AdaBooost and multiple linear regression. We obtained 77.5% as the accuracy by the AdaBoost and 0.649 as the adjusted R 2 by the regression.

[1]  Yoshifumi Kitamura,et al.  A Study of Nonverbal Cues and Subjective Atmosphere in Six Person Conversations , 2012 .

[2]  อนิรุธ สืบสิงห์,et al.  Data Mining Practical Machine Learning Tools and Techniques , 2014 .

[3]  Omura Mai,et al.  Estimation of Subjective Impressions of Difficulty in Quiz Dialogue , 2013 .

[4]  Rosalind W. Picard,et al.  Automated Posture Analysis for Detecting Learner's Interest Level , 2003, 2003 Conference on Computer Vision and Pattern Recognition Workshop.

[5]  Masayuki Murakami,et al.  Estimating Learners ’ Subjective Impressions of the Difficulty of Course Materials in e-Learning Environments , 2008 .

[6]  Kristy Elizabeth Boyer,et al.  Analyzing Posture and Affect in Task-Oriented Tutoring , 2012, FLAIRS Conference.

[7]  Junji Yamato,et al.  Linking speaking and looking behavior patterns with group composition, perception, and performance , 2012, ICMI '12.

[8]  Kazutaka Shimada,et al.  A Person Identification Method Using a Top-View Head Image from an Overhead Camera , 2012, J. Adv. Comput. Intell. Intell. Informatics.

[9]  Peter Robinson,et al.  3D Corpus of Spontaneous Complex Mental States , 2011, ACII.

[10]  Yoav Freund,et al.  Experiments with a New Boosting Algorithm , 1996, ICML.

[11]  C. Hmelo‐Silver.  Problem-Based Learning: What and How Do Students Learn? , 2004 .

[12]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[13]  Aiko M. Hormann,et al.  Programs for Machine Learning. Part I , 1962, Inf. Control..

[14]  Marjorie Fink Vargas,et al.  Louder than words : an introduction to nonverbal communication , 1986 .

[15]  Kazutaka Shimada,et al.  Person Identification Using Top-View Image with Depth Information , 2012, 2012 13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing.

[16]  Junji Yamato,et al.  Analyzing perceived empathy/antipathy based on reaction time in behavioral coordination , 2013, 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG).

[17]  Ian H. Witten,et al.  Chapter 1 – What's It All About? , 2011 .

[18]  Shimada Kazutaka,et al.  Hot spot detection in multi-party conversation using laughing feature , 2012 .

[19]  Shimada Kazutaka,et al.  Posture identification for evaluation of multi-party interaction , 2012 .