Abstract
We propose a method for estimating the students’ posture sequence in classroom from video footage by computer automatically. A posture sequence is a time-series of student’s postures during a lecture and a posture of a student is described by a set of his head, body trunk (torso) and hands/arms states, which we call the body part states. The detection of body parts from video footage has many errors. To cope with the errors, we introduce spatio-temporal constraints, in which we propagate the belief of postures through a given time interval with considering the confidence of observation. Through this propagation, we can revise the erroneous detection results and estimate an appropriate posture sequence. In the experiment, we apply our proposed method to a real lecture, and show that our method can improve the accuracy of posture sequence estimation.
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Mukunoki, M., Yoshitsugu, K., Minoh, M. (2012). Students’ Posture Sequence Estimation Using Spatio-temporal Constraints. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances in Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 298. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31715-6_44
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DOI: https://doi.org/10.1007/978-3-642-31715-6_44
Publisher Name: Springer, Berlin, Heidelberg
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