This paper introduces an interactive expression editing system that allows users to design facial expressions easily. Currently, popular example-based methods construct face models based on the examples of target face. The shortcoming of these methods is that they cannot create expressions for novel faces: target faces not previously recorded in the database. We propose a solution to overcome this limitation. We present an interactive facial-geometric-feature animation system for generating expressions of novel faces. Our system is easy to use. By click-dragging control points on the target face, on the computer screen display, unique expressions are generated automatically. To guarantee natural animation results, our animation model employs prior knowledge based on various individuals' expressions. One model prior is learned from motion vector fields to guarantee effective facial motions. Another, different, model prior is learned from facial shape space to ensure the result has a real facial shape. Interactive animation problem is formulated in a maximum a posterior (MAP) framework to search for optimal results by combining the priors with user-defined constraints. We give an extension of the Motion Propagation (MP) algorithm to infer facial motions for novel target faces from a subset of the control points. Experimental results on different facial animations demonstrate the effectiveness of the proposed method. Moreover, one application of our system is exhibited in this paper, where users create expressions for facial sketches interactively.

We present here a simple technique for parametrization of popular biorthogonal wavelet filter banks (BWFBs) having vanishing moments (VMs) of arbitrary multiplicity. Given a prime wavelet filter with VMs of arbitrary multiplicity, after formulating it as a trigonometric polynomial depending on two free parameters, we prove the existence of its dual filter based on the theory of Diophantine equation. The dual filter permits perfect reconstruction (PR) and also has VMs of arbitrary multiplicity. We then give the complete construction of two-parameter families of 17/11 and 10/18 BWFBs, from which any linear-phase 17/11 and 10/18 BWFB possessing desired features could be derived with ease by adjusting the free parameters. In particular, two previously unpublished BWFBs for embedded image coding are constructed, both have optimum coding gains and rational coef ficients. Extensive experiments show that our new BWFBs exhibit performance equal to Winger's W-17/11 and Villasenor's V-10/18 (superior to CDF-9/7 by Cohen et al. and Villasenor's V-6/10) for image compression, and yet require slightly lower computational costs.