Abstract
In this paper, a single camera and a dual prism are integrated to implement a three-dimensional face recognition system. The proposed system is implemented on an embedded development platform named UBIKIT6612. A dual prism placed in front of the camera is used to simulate human binocular vision. We then used the active appearance models (AAM) to find out the corresponding feature points and calculate the depth of the face by stereo vision. Accordingly, three-dimensional facial model of each member is constructed. Facial features extracted from the 3D facial models are used for identification. To promote the recognition accuracy, we first exclude most of non-members by support vector data description (SVDD), followed by conducting a multi-class support vector machines (SVM) for face recognition. Experimental results show that the proposed method of the exclusion of non-members works more efficiently than those of traditional methods.
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Chang, CY., Chang, CW., Chang, MC. (2014). An Embedded 3D Face Recognition System Using a Dual Prism and a Camera. In: Pan, JS., Krömer, P., Snášel, V. (eds) Genetic and Evolutionary Computing. Advances in Intelligent Systems and Computing, vol 238. Springer, Cham. https://doi.org/10.1007/978-3-319-01796-9_17
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DOI: https://doi.org/10.1007/978-3-319-01796-9_17
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-01795-2
Online ISBN: 978-3-319-01796-9
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