• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.228-246
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• 2011

A 3D model based approach for a face representation and recognition algorithm has been investigated as a robust solution for pose and illumination variation. Since a generative 3D face model consists of a large number of vertices, a 3D model based face recognition system is generally inefficient in computation time and complexity. In this paper, we propose a novel 3D face representation algorithm based on a pixel to vertex map (PVM) to optimize the number of vertices. We explore shape and texture coefficient vectors of the 3D model by fitting it to an input face using inverse compositional image alignment (ICIA) to evaluate face recognition performance. Experimental results show that the proposed face representation and recognition algorithm is efficient in computation time while maintaining reasonable accuracy.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.440-451
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• 2019

We propose a system that allows three dimensional manipulation of face in video. The 3D face manipulation of the proposed system overlays the 3D face model with the user 's manipulation on the face region of the video frame, and it allows 3D manipulation of the video in real time unlike existing applications or methods. To achieve this feature, first, the 3D morphable face model is registered with the image. At the same time, user's manipulation is applied to the registered model. Finally, the frame image mapped to the model as texture, and the texture-mapped and deformed model is rendered. Since this process requires lots of operations, parallel processing is adopted for real-time processing; the system is divided into modules according to functionalities, and each module runs in parallel on each thread. Experimental results show that specific parts of the face in video can be manipulated in real time.