Adaptive Processing of Range Scanned Head: Synthesis of Personalized Animated Human Face Representation with Multiple-Le
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Research Article Adaptive Processing of Range Scanned Head: Synthesis of Personalized Animated Human Face Representation with Multiple-Level Radial Basis Function C. Chen1 and Edmond C. Prakash2 1 School
of Computer Engineering, Nanyang Technological University, Nanyang Avenue, Singapore 639798 of Computing and Mathematics (DOCM), Manchester Metropolitan University, Chester Street, Manchester M1 5GD, UK
2 Department
Received 6 February 2006; Revised 29 July 2006; Accepted 10 September 2006 Recommended by Ming Ouhyoung We propose an animation system for personalized human head. Landmarks compliant to MPEG-4 facial definition parameters (FDP) are initially labeled on both template model and any target human head model as priori knowledge. The deformation from the template model to the target head is through a multilevel training process. Both general radial basis function (RBF) and compactly supported radial basis function (CSRBF) are applied to ensure the fidelity of the global shape and face features. Animation factor is also adapted so that the deformed model still can be considered as an animated head. Situations with defective scanned data are also discussed in this paper. Copyright © 2007 Hindawi Publishing Corporation. All rights reserved.
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INTRODUCTION
Many research efforts have been focused on the achievement of realistic representation of human face since the pioneer work of Parke [1]. However, the complex facial anatomical structure and various facial tissue behavior make it still a formidable challenge in computer graphics area. The animated head system can find place in multimedia applications, including human-computer interaction, video conference system, and entertainment industry. For traditional facial shape modeling, we need a skilled modeler to spend a lot of time on building the model from scratch. With the availability of range scanners, the shape information is already easily obtainable in seconds. Figure 1 shows a scanned face from our range scanner, but this method still suffers from the following problems. Shape problem From the range scanned data, the smoothness of the reconstructed data is still not complete. Holes or gap may appear during the merge procedure of two scanned data from different views. Overlapped or folded surfaces produced by merge procedure results in visual artifact. One particular problem in facial data acquisition by range scanning method is that hairy surface cannot be appropriately recognized by the scanner.
Manual editing Facial shape is not a totally continuous isosurface, it contains some feature parts such as lips, eyes, and nostril. In a neutral face, the mouth is closed, the eye gaze direction is towards the front, and the nostril is invisible. The range scanner does not have the capability to detect these features, so tedious manual editing effort such as lip contour separation is still required. Animation ready Even as the precision of the scanner is increasing, modeling the portion of head other than the face can be solved by scanning a head with very sho
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