Circular Interpolation for Morphing 3D Facial Animations (original) (raw)
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Computer facial animation is not a new endeavour as it had been introduced since 1970s. However, animating human face still presents interesting challenges because of its familiarity as the face is the part used to recognize individuals. Facial modelling and facial animation are important in developing realistic computer facial animation. Both modelling and animation is dependent to drive the animation. This paper reviews several geometric-based modelling (shape interpolation, parameterization and muscle-based animation) and data-driven animation (image-based techniques speech-driven techniques and performance-driven animation) techniques used in computer graphics and vision for facial animation. The main concepts and problems for each technique are highlighted in the paper.
A major unsolved problem in computer graphics is the construction and animation of realistic human facial models. Traditionally, facial models have been built painstakingly by manual digitization and animated by adhoc parametrically controlled facial mesh deformations or kinematic approximation of muscle actions. Fortunately, animators are now able to digitize facial geometries through the use of scanning range sensors and animate them through the dynamic simulation of facial tissues and muscles. However, these techniques require considerable user input to construct facial models of individuals suitable for animation. Realistic facial animation is achieved through geometric and image manipulations. Geometric deformations usually account for the shape and deformations unique to the physiology and expressions of a person. Image manipulations model the reflectance properties of the facial skin and hair to achieve smallscale detail that is difficult to model by geometric manipulation alone.
Shape Interpolation with Multiresolution Analysis
This paper presents a novel approach for shape interpolation in 3D morphing with irregular meshes. We assume that the metameshes of the source and target meshes are given. The basic idea is that the multiresolution analysis of metameshes with detail encoding helps to generate natural in-between meshes. We construct mesh hierarchies by simplifying the given metameshes to the base meshes with the error metric reflecting both the source and target geometry. The geometric differences between successive levels in the hierarchies are encoded as details represented in local frames. An in-between mesh is synthesized by adding up the blended details to the interpolated base mesh. Experimental results demonstrate that the generated in-between meshes have reasonable blended shapes of the source and target meshes.
LITERATURE REVIEW OF FACIAL MODELING AND ANIMATION TECHNIQUES
A major unsolved problem in computer graphics is the construction and animation of realistic human facial models. Traditionally, facial models have been built painstakingly by manual digitization and animated by adhoc parametrically controlled facial mesh deformations or kinematic approximation of muscle actions. Fortunately, animators are now able to digitize facial geometries through the use of scanning range sensors and animate them through the dynamic simulation of facial tissues and muscles. However, these techniques require considerable user input to construct facial models of individuals suitable for animation. Realistic facial animation is achieved through geometric and image manipulations. Geometric deformations usually account for the shape and deformations unique to the physiology and expressions of a person. Image manipulations model the reflectance properties of the facial skin and hair to achieve smallscale detail that is difficult to model by geometric manipulation alone.
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The problems that are often encountered in the making of facial expressions on 3D animated avatars heavily dependent on the ability of key animators to create movement and combine them into a series of facial motion animation. This research proposes an automatic preprocessing for facial animation using feature point cluster. The mechanism of a transfer system for animated facial expressions using a radial basis function technique that is effective, especially in terms of production speed. This study focuses on the improvement of animated facial expressions using the feature point cluster. The result is to provide improved motion animation more expressive. This process will be easier and faster for the formation of facial motion animation without the need for process adjustments manually.
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The facial animation in term of 3D facial data has accurate research support of the laser scan and advance 3D tools for complex facial model production. However, the approach still lacks facial expression based on emotional condition. Though, facial skin colour is required to offers an effect of facial expression improvement, closely related to the human emotion. This paper presents innovative techniques for facial animation transformation using the facial skin colour based on linear interpolation and bilinear interpolation. The generated expressions are almost same to the genuine human expression and also enhance the facial expression of the virtual human.