Example-based caricature generation with exaggeration control

Caricature is a popular artistic media widely used for effective communications. The fascination of caricature lies in its expressive depiction of a person’s prominent features, which is usually realized through the so-called exaggeration technique. This paper proposes a new example-based automatic caricature generation system supporting the exaggeration of both the shape of facial components and the spatial relationships among the components. Given the photograph of a face, the system automatically computes the feature vectors representing the shape of facial components as well as the spatial relationship among the components. Those features are exaggerated and then used to search the learning database for the corresponding caricature components and for arranging the retrieved components to create the caricature. Experimental results show that our system can generate the caricatures of the example style capturing the prominent features of the subjects.     

Interactive 3D caricature from harmonic exaggeration

A common variant of caricature relies on exaggerating characteristics of a shape that differs from a reference template, usually the distinctive traits of a human portrait. This work introduces a caricature tool that interactively emphasizes the differences between two three-dimensional meshes. They are represented in the manifold harmonic basis of the shape to be caricatured, providing intrinsic controls on the deformation and its scales. It further provides a smooth localization scheme for the deformation. This lets the user edit the caricature part by part, combining different settings and models of exaggeration, all expressed in terms of harmonic filter. This formulation also allows for interactivity, rendering the resulting 3d shape in real time.     

Shape-based detail-preserving exaggeration of extremely accurate 3D faces

We present an approach to automatically exaggerate the distinctive features of extremely detailed 3D faces. These representations comprise several million triangles and capture skin detail down to the pores. Despite their high level of realism, their size makes visualization difficult and real-time mesh manipulation infeasible. The premise of our methodology is to first remove the detail to obtain low resolution shape information, then perform shape-based exaggeration on a low resolution model and finally reapply the detail onto the exaggeration to recover the original resolution. We also present the results of applying this methodology to a small set of faces.     

3D facial model exaggeration builder for small or large sized model manufacturing

An action figure is a small human-shaped object used as a toy for children or artistic collection. In the past, the creation of action figures required intense manual effort. An initial trial to automate the process using recent scanning technology failed to yield figures with market appeal because the resulting action figures did not have sufficiently life-like shapes and expressions. The limiting factor which was not considered during this trial is the loss of individual characteristics resulting from either an increase or reduction in scale. We provide novel techniques for creating an exaggerated human face that retains all of the skin detail in the 3D scanned model, which will allow more characteristic figures to be easily created at any scale, thereby saving money and time during manufacturing. While traditional 3D printing applications utilize rigid models acquired using computer-aided design, our method demonstrates that deformable models (such as a human face) obtained from scanners are also suitable.

An automatic method for motion capture-based exaggeration of facial expressions with personality types

Facial expressions have always attracted considerable attention as a form of nonverbal communication. In visual applications such as movies, games, and animations, people tend to be interested in exaggerated expressions rather than regular expressions since the exaggerated ones deliver more vivid emotions. In this paper, we propose an automatic method for exaggeration of facial expressions from motion-captured data with a certain personality type. The exaggerated facial expressions are generated by using the exaggeration mapping (EM) that transforms facial motions into exaggerated motions. As all individuals do not have identical personalities, a conceptual mapping of the individual’s personality type for exaggerating facial expressions needs to be considered. The Myers–Briggs type indicator, which is a popular method for classifying personality types, is employed to define the personality-type-based EM. Further, we have experimentally validated the EM and simulations of facial expressions.     

Automatic stress exaggeration by prosody modification to assist language learners perceive sentence stress

In this paper, we propose a set of automatic stress exaggeration methods that can enlarge the differences between stressed and unstressed syllables. Our stress exaggeration methods can be used in computer-aided language learning systems to assist second language learners perceive stress patterns. The intention of our automatic stress exaggeration methods is to support hyper-pronunciation training which is commonly used in classrooms by teachers. In hyper-pronunciation training, exaggeration is used to help learners increase their awareness of acoustic features and effectively apply these features into their pronunciation. Duration, pitch and intensity have been claimed to be the main acoustic features that are closely related to stress in English language. Thus, four stress exaggeration methods are proposed in this paper: (i) duration-based stress exaggeration, (ii) pitch-based stress exaggeration, (iii) intensity-based stress exaggeration, and (iv) a combined stress exaggeration method that integrates the duration-based, pitch-based and intensity-based exaggeration methods. Our perceptual experimental results show that resynthesised stimuli by our proposed stress exaggerated methods can help learners of English as a Second Language (ESL) better perceive English stress patterns significantly.     

Constructing control rules for a dynamic system: probabilistic qualitative models,lookahead and exaggeration

Dynamic systems have sometimes to be controlled in circumstances that are very inconvenient for classical control methods. In such cases, use of qualitative controllers seems to be a promising alternative, as they can be designed without having an exact mathematical model. A method for synthesizing control rules is presented, in which a probabilistic qualitative model is used together with a decision strategy that takes into account the results of qualitative simulation. As a case study, the problem of the inverted pendulum control is considered. By combining the model simulation lookahead and a decision criterion, an interesting phenomenon of ‘exaggerated simulation’ has emerged. Experimental results show that in certain cases, using an exaggerated force in the process of simulation considerably improves the performance of generated control rules. The exaggeration helps to detect some trends of the system's behaviour that would otherwise have remained hidden. Experiments and mathematical analysis show that the improvement due to the exaggeration is comparable to that achieved by a deeper lookahead in the state transition graph.     

Efficient shape matching using shape contexts

We demonstrate that shape contexts can be used to quickly prune a search for similar shapes. We present two algorithms for rapid shape retrieval: representative shape contexts, performing comparisons based on a small number of shape contexts, and shapemes, using vector quantization in the space of shape contexts to obtain prototypical shape pieces.     

Measuring biological shape using geometry-based shape transformations

This paper presents a methodology for shape analysis of anatomical structures. A template shape is used as a unit, and a shape transformation mapping the template to a particular structure is used to quantify the shape of the structure with respect to the template. The geometric characteristics of the boundaries of the template and the individual structure are used to define point correspondences between the template and the structure. These correspondences are then used to determine the shape transformation, which is based on an elastic adaptation of the template. Regional inter-subject and inter-population shape differences are then identified by comparing the corresponding shape transformations point-wise. Validation using simulation experiments is also presented.     

基于多尺度形状分析的叶形识别系统

叶形自动识别系统使用一种改进了的边界跟踪算法检测叶片边界,应用多尺度形状分析技术有效地提取出规范锯齿长度和曲率尺度空间图像极大值点集两个曲率特征。综合叶片的离心率、似圆率和这两个边界曲率特征来检索叶片数据库,进行形状匹配,实现叶片自动分类。实验结果表明,该系统使用的技术能大幅提高叶形识别的精确率和检索率。     

Planar shape matching based on binary tree shape representation

In this paper we suggest a new way of representing planar two-dimensional shapes and a shape matching method which utilizes the new representation. Through merging of the neighboring boundary runs, a shape can be partitioned into a set of triangles. These triangles are inherently connected according to a binary tree structure. Here we use the binary tree with the triangles as its nodes to represent the shape. This representation is found to be insensitive to shape translation, rotation, scaling and skewing changes due to viewer's location changes (or the object's pose changes). Furthermore, the representation is of multiresolution.

In shape matching we compare the two trees representing two given shapes node by node according to the breadth-first tree traversing sequence. The comparison is done from top of the tree and moving downward, which means that we first compare the lower resolution approximations of the two shapes. If the two approximations are different, the comparison stops. Otherwise, it goes on and compares the finer details of the two shapes. Only when the two shapes are very similar, will the two corresponding trees be compared entirely. Thus, the matching algorithm utilizes the multiresolution characteristic of the tree representation and appears to be very efficient.     

Hand shape recognition based on coherent distance shape contexts

In this paper, we propose a novel hand shape recognition method named as Coherent Distance Shape Contexts (CDSC), which is based on two classical shape representations, i.e., Shape Contexts (SC) and Inner-distance Shape Contexts (IDSC). CDSC has good ability to capture discriminative features from hand shape and can well deal with the inexact correspondence problem of hand landmark points. Particularly, it can extract features mainly from the contour of fingers. Thus, it is very robust to different hand poses or elastic deformations of finger valleys. In order to verify the effectiveness of CDSC, we create a new hand image database containing 4000 grayscale left hand images of 200 subjects, on which CDSC has achieved the accurate identification rate of 99.60% for identification and the Equal Error Rate of 0.9% for verification, which are comparable with the state-of-the-art hand shape recognition methods.     

A shape synthesizer

The article discusses a new shape synthesizer that fosters creative 3D modeling of shapes difficult to develop without a computer. It builds on principles from sound synthesis, mapping them directly into 3D geometry. The article focuses on creative and expressive modeling and development rather than faithfully representing manufacturing processes. The modeling environment lets a designer interactively develop and refine models based on aesthetic judgement applied during the modeling process     

Detail-replicating shape stretching

Mesh deformation has become a powerful tool for creating shape variations. Existing deformation techniques work on preserving surface details under bending and twisting operations. Stretching different parts of a shape is also a useful operation for generating shape variations. However, under stretching, texture-like geometric details should not be preserved but rather replicated. We propose a simple and efficient method that helps create model variations by applying nonuniform stretching on 3D models with organic geometric details. The method replicates the geometric details and synthesizes extensions by adopting texture synthesis techniques on surface details. We work on analyzing and separating the stretching of surface details from the stretching of the base mesh resulting in the appearance of preserved details. The efficiency of our method is attributed to a local parameterization of the surface with the help of curve skeletons. We show a variety of experimental results that demonstrate the usefulness of this intuitive stretching tool in creating shape variations.     

Zometool shape approximation

We present an algorithm that approximates 2-manifold surfaces with Zometool models while preserving their topology. Zometool is a popular hands-on mathematical modeling system used in teaching, research and for recreational model assemblies at home. This construction system relies on a single node type with a small, fixed set of directions and only 9 different edge types in its basic form. While being naturally well suited for modeling symmetries, various polytopes or visualizing molecular structures, the inherent discreteness of the system poses difficult constraints on any algorithmic approach to support the modeling of freeform shapes. We contribute a set of local, topology preserving Zome mesh modification operators enabling the efficient exploration of the space of 2-manifold Zome models around a given input shape. Starting from a rough initial approximation, the operators are iteratively selected within a stochastic framework guided by an energy functional measuring the quality of the approximation. We demonstrate our approach on a number of designs and also describe parameters which are used to explore different complexities and enable coarse approximations.     

Scale-aware shape manipulation

A novel representation of a triangular mesh surface using a set of scale-inva~iant measures is proposed. The measures consist of angles of the triangles （triangle angles） and dihedral angles along the edges （edge angles） which are scale and rigidity independent. The vertex coordinates for a mesh give its scale-invariant measures, unique up to scale, rotation, and translation. Based on the representation of mesh using scale-invariant measures, a two-step iterative deformation algorithm is proposed, which can arbitrarily edit the mesh through simple handles interaction. The algorithm can explicitly preserve the local geometric details as much as possible in different scales even under severe editing operations including rotation, scaling, and shearing. The efficiency and robustness of the proposed algorithm are demonstrated by examples.