Abstract | ||
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Affective information is vital for effective human-to- human communication. Likewise, human-to-computer communi- cation could be potentiated by an "affective barometer" able to infer human affect using a machine vision system. For instance, during a classroom lecture, an affective barometer might provide useful feedback that a real or virtual instructor could use to improve pedagogical strategies. In this paper, we explore the feasibility of using students' unintentional hand gestures during a classroom lecture to predict their affective state. We propose a maximum a posteriori classifier based on a simple Bayesian network model. We then evaluate the classifier's ability to predict one of four affective states from five hand gestures observed in video recordings of a classroom lecture. Using four-fold cross validation, we find that the model's generalization accuracy is 100% over cases where the student reported an affective state, and 79.4% when we include cases where the student reported no affective state. The experiment demonstrates that there is a strong relationship between human affect and visually observable gestures. Future work will explore the applicability of these results in practical applications. Index Terms— Behavior recognition, Intelligent tutoring sys- tems, Human-computer interaction, Probabilistic affect predic- tion, Unintentional hand gestures. |
Year | Venue | Keywords |
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2008 | ARCS | machine vision,indexing terms,human computer interaction,cross validation,bayesian network |
Field | DocType | Citations |
Computer science,Gesture,Real-time computing,Human–computer interaction,Artificial intelligence,Probabilistic logic,Classifier (linguistics),Machine vision system,Bayesian network,Maximum a posteriori estimation,Affect (psychology),Cross-validation,Machine learning | Conference | 0 |
PageRank | References | Authors |
0.34 | 10 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Abdul Rehman Abbasi | 1 | 46 | 3.33 |
Matthew N. Dailey | 2 | 331 | 26.44 |
Nitin V. Afzulpurkar | 3 | 50 | 5.44 |
Takeaki Uno | 4 | 1319 | 107.99 |