Abstract
Active Appearance Model (AAM) is a generic model for the certain visual phenomena, and one of the powerful modeling techniques in the image processing area. AAM has been initially developed for the face modeling. Recently, it is shown that it may be useful for other area. In this paper, we first present how to use AAM in facial expression recognition and then extend it to the left ventricle segmentation problem. For the former, we establish face model using Cohn-Kanade facial expression database, whereas for the latter, SPEC images will be used for modeling the left ventricle. We show that the facial expression model can continuously track human facial expressions, and the left ventricle model can segment the inside and outside of the left ventricle. Our examples can be extended to other medical applications.
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Cho, KS., Choi, SM., Kim, YG. (2007). Tracking and Segmenting Diverse Objects Using Active Appearance Model. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Contemporary Intelligent Computing Techniques. ICIC 2007. Communications in Computer and Information Science, vol 2. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74282-1_152
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DOI: https://doi.org/10.1007/978-3-540-74282-1_152
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74281-4
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