21281832
Progressive mesh metamorphosis
This paper describes a new integrated scheme for metamorphosis between two closed manifold genus-0 polyhedral models. Spherical parameterizations of the source and target models are created first. To control the morphing, any number of feature vertex pairs is specified and a fold-over free warping method is used to align two spherical embeddings. Our method does not create a merged meta-mesh or execute re-meshing to construct a common connectivity for morphs. Alternatively, a scheme for the progressive connectivity transformation of two spherical parameterizations is employed to generate the intermediate meshes. A novel semi-overlay with a geomorph scheme is proposed to reduce the popping effects caused by the connectivity transformation. We demonstrate several examples of aesthetically pleasing morphing sequences using the proposed scheme. Copyright © 2005 John Wiley & Sons, Ltd.
28008024
Multiresolution Remeshing Using Weighted Centroidal Voronoi Diagram
We present a novel method for multiresolution remeshing of irregular mesh. First, the original mesh (two-manifold any genus) is decomposed into several patches, each patch is homeomorphic to a 2D triangle. The goal of this decomposition process is that the decomposed patches are size-equally. First, a mesh is manually cut into a few disk-like patches. With the help of weighted centroidal Voronoi diagram (WCVD), each patch is then automatically partitioned into more triangular patches with nearly equal size. Recursively subdividing these triangular patches, we finally get a semi-regular mesh.
12361441
Computer-aided prototype system for nose surgery
Rhinoplasty, or surgery to reshape the nose, is one of the most common of all plastic-surgery procedures. Rhinoplasty can enhance a patient's appearance and self-confidence, may also correct a birth defect or injury, or help relieve some breathing problem. In this paper, we present a three-dimensional (3-D) surgical simulation system, which can assist surgeons in planning rhinoplasty procedures. This system employs computer graphics and image-processing techniques for the simulation of a rhinoplasty. Although the presented algorithms themselves are not new, the proposed system exploits the new idea to apply 3-D morphing for rhinoplasty, and simulation results are useful for the physicians. According to patients' expectation of what they would like their noses to look like, our system simulates expected results. Our tools provide quantitative measurements of a nose structure. Using these quantitative results, surgeons can arrange appropriate preoperative plans for patients. Finally, experimental results and experiences are reported to evaluate the usefulness of the proposed system.
14075649
Nonparametric log spectrum estimation using disconnected regression splines and genetic algorithms
This article proposes a new nonparametric procedure for estimating log spectra. This procedure consists of three major components: (1) a novel statistical model for modelling the unknown target log spectrum, (2) an AIC-based model selection criterion for choosing a 'best' fitting model, and (3) a genetic algorithm for effectively searching the 'best' fitting model. Numerical experiments are conducted to evaluate and compare the practical performance of the proposed procedure with some other common log spectral estimation procedures appearing in the literature. These other procedures include wavelet techniques, kernel smoothing and regression spline fitting. Empirical results suggest that the proposed procedure compares favourably against all these procedures, especially when the unknown log spectrum contains inhomogeneous structures.
76211
Negative weights make adversaries stronger
The quantum adversary method is one of the most successful techniques for proving lower bounds on quantum query complexity. It gives optimal lower bounds for many problems, has application to classical complexity in formula size lower bounds, and is versatile with equivalent formulations interms of weight schemes, eigen values, and Kolmogorov complexity. All these formulations rely on the principlethat if an algorithm successfully computes a function then, in particular, itis able to distinguish between inputs which map to different values.
 We present a stronger version of the adversary method which goes beyond this principle to make explicit use of the stronger condition that the algorithm actually computes the function. This new method, which we call ADV+-, has all the advantages ofthe old: it is a lower bound on bounded-error quantum query complexity, its square is a lower bound on formula size, and it behaves well with respect tofunction composition. Moreover ADV+- is always at least as large as the adversary method ADV, and we show an example of a monotone function forwhich ADV+-(f)=Omega(ADV(f)1.098). We also give examples showing that ADV+- does not face limitations of ADV like the certificate complexity barrier and the property testing barrier.
9084974
Isolated word recognition using modular recurrent neural networks
Abstract This paper describes a novel method of using recurrent neural networks (RNN) for isolated word recognition. Each word in the target vocabulary is modeled by a fully connected recurrent network. To recognize an input utterance, the best matching word is determined based on its temporal output response. The system is trained in two stages. First, the RNN speech models (RSM) are trained independently to capture the essential static and temporal characteristics of individual words. This is performed by using an iterative re-segmentation training algorithm which gives the optimal phonetic segmentation automatically for each training utterance. The second-stage involves mutually discriminative training among the RSMs, aiming at minimizing the probability of misclassification. A series of simulation experiments have been performed to demonstrate the effectiveness of the proposed recognition method. For the recognition of (A) 20 English words, (B) 11 Cantonese digits and (C) 58 Cantonese CV syllables, the top-1 accuracy are 91.9, 93.6 and 87.1%, respectively.
7135959
On original generation of structure in legal documents
This position paper advocates a vision in the development of automated legal reasoning and presents evidence supporting the plausibility of that vision. The paper observes that original creation of documents of legal import in either fully formal or semistructured form offers the prospect of greatly reducing the cost and expanding the scope of knowledge engineering for legal reasoning. This, it is claimed, is most likely to be achieved via formalization of various sublanguages of legal discourse. SeaSpeak is an example of such a sublanguage and it appears to be amenable to full formalization. Short of that, much can be done with partial formalization and semistructured documents. The paper presents a tabular format for message expression, motivated by a formal agent communication language.
207726294
Evolving better population distribution and exploration in evolutionary multi-objective optimization
The aim of multi-objective evolutionary optimization is to minimize the distance between the solution set and the true Pareto front, to distribute the solutions evenly and to maximize the spread of solution set. This paper addresses these issues by presenting two features that enhance the optimization ability of multi-objective evolutionary algorithms. The first feature is a variant of the mutation operator that adapts the mutation rate along the evolution process to maintain a balance between the introduction of diversity and local fine-tuning. In addition, this adaptive mutation operator adopts a new approach to strike a compromise between the preservation and disruption of genetic information. The second feature is an enhanced exploration strategy that encourages the exploration towards less populated areas and hence achieves better discovery of gaps in the generated front. The strategy also preserves non-dominated solutions in the evolving population to achieve a good convergence for the optimization. Comparative studies of some well-known diversity operators, mutation operators and multi-objective evolutionary algorithms are performed on different benchmark problems, which illustrate the effectiveness and efficiency of the proposed features.