NASA Tech Briefs, March 1995

This issue contains articles with a special focus on Computer-Aided design and engineering amd a research report on the Ames Research Center. Other subjects in this issue are: Electronic Components and Circuits, Electronic Systems, Physical Sciences, Materials, Computer Programs, Mechanics, Machinery, Manufacturing/Fabrication, Mathematics and Information Sciences and Life Science

Methods for Procedural Terrain Generation

Procedural generation has been utilized in the automatic generation of data for a long time. This automated processing has been utilized in the entertainment industry as well as in research work in order to be able to quickly produce large amounts of just the kind of data needed, for example, in system testing. In this thesis, we examine different ways to utilize procedural generation to produce different synthetic terrains. First, we will take a closer look at what procedural generation is, where it originally started, and where it was utilized. From this we move on to look at how this technology is utilized in the creation of terrains and what terrain is generally visually required. From this we move on to look at different ways to implement terrain generation. As part of this thesis, we have selected three methods and implemented our own implementations for terrain generation. We look at the performance of these implementations, and what a test group thinks about those synthetic terrains. The results obtained from this are analyzed and presented at the end of the thesis.Proseduraalista generointia on hyödynnetty datan automaattisessa tuottamisessa jo pitkään. Tätä automatisoitua prosessointia on niin hyödynnetty viihdeteollisuudessa kuin tutkimustyössä, jotta ollaan voitu tuottaa nopeasti suuria määriä juuri sellaista dataa kuin tarvitaan esimerkiksi järjestelmän testauksessa. Tässä tutkielmassa tarkastellaan erilaisia tapoja hyödyntää proseduraalista generointia erilaisten synteettisten maastojen tuottamiseksi. Aluksi tutustutaan hieman tarkemmin siihen mitä proseduraalinen generointi on, mistä se on alunperin lähtenyt ja mihin sitä on hyödynnetty. Tästä siirrytään tarkastelemaan miten kyseistä tekniikkaa hyödynnetään maastojen luomisessa ja mitä maastoilta yleensä visuaalisesti vaaditaan. Tästä siirrytään tarkastelemaan eri tapoja toteuttaa maaston generointia. Osana tätä tutkielmaa, on valittu kolme menetelmää ja laadittu niistä kullekin oma toteutus maaston generointiin. Työssä tarkastellaan näiden toteutusten suoritustuloksia, ja mitä mieltä testiryhmä on kyseisistä synteettisistä maastoista. Saadut tulokset ja niiden analyyysi esitellään tutkielman lopussa

Towards procedural music-driven animation: exploring audio-visual complementarity

Master dissertation (Master Degree in Computer Science)This thesis intends to describe our approach towards developing a framework for the interactive creation of music driven animations. We aim to create an integrated environment where real-time musical information is easily accessible and is able to be flexibly used for manipulating different aspects of a reactive simulation. Such modifications are specified through the use of a scripting language and include, for instance, geometrical transformations and geometry synthesis, gradual colour changes as well as the application of arbitrary forces. Our framework thus represents a proof-of-concept for converting musical information into arbitrary modifications to a dynamic simulation, producing a variety of animations. This is possible due to a bargaining between control and automation, where control is present by allowing the user to program these modifications with a scripting language and automation is present by using physics and interpolation to estimate the visual effects resulting from those modifications. The particular test case for our system was the animation/simulation of a growing tree reacting to wind. In order to control or influence both the tree growth and wind field, as well as other visual parameters, the system accepts two different but complementary representations of music: a MIDI event stream and raw audio data. Different musical features are obtainable from each of these representations. On one hand, by using MIDI, we are able to discretely synchronise visual effects with the basic elements of music, such as the sounding of notes or chords. On the other, using audio, we are able to produce continuous changes by obtaining numerical data from basic spectral analysis. Our framework provides a common interface for the combined application of these different sources of musical information to the generation of visual imagery, under the form of procedural animations. We will describe algorithms presented in multiple research papers, namely for tree generation, wind field generation and tree reaction to wind, briefly detailing our implementation and architecture. We also describe why each of these particular methods was chosen, how they are organised in our platform and how their parameters may be modified from our scripting environment leading to what we regard as the procedural generation of animations. By allowing the user to access musical information and give them control of what we have come to refer to as animation primitives, such as wind and tree growth, we believe to have taken a first step towards exploring a novel concept with a seemingly endless expressive potential.Esta dissertação descreve o desenvolvimento de uma plataforma para a criação interativa de animações dirigidas por música. Focamo-nos em desenvolver um ambiente integrado onde vários aspetos de uma animação podem ser controlados pelo processamento em tempo real de informação musical, com recurso a uma linguagem de script. O caso de teste específico da nossa aplicação consiste na animação de uma árvore em crescimento capaz de reagir a um campo de vento dinâmico. De forma a controlar ou influenciar quer o crescimento da árvore, quer o campo de vento, o sistema aceita como input duas representações diferentes, mas complementares, de música, uma sequência contínua de eventos MIDI e áudio. Realçamos a distinção entre estas duas representações visto que apesar de serem ambas referentes a música, são fundamentalmente diferentes em termos da informação que contêm. Eventos MIDI contêm informação simbólica relativa à interpretação da música, nomeadamente os tempos de começo e final de notas. Por outro lado, informação áudio consiste num sinal contínuo, que resulta da gravação de um instrumento ou de uma atuação musical. Com MIDI, a nossa plataforma é capaz de sincronizar alterações discretas à simulação, com base nos elementos fundamentais da teoria musical, como o soar de notas ou acordes. Com informação áudio, é possível produzir alterações contínuas com base nos dados numéricos obtidos por análise espectral elementar do sinal de áudio. Neste documento serão descritos vários algoritmos apresentados em artigos de investigação, nomeadamente para a geração de árvores, geração de campos de vento e reação da árvore ao vento. Iremos descrever os motivos que levaram à sua escolha, a sua organização na nossa plataforma e os vários parâmetros que podemos modificar a partir do nosso ambiente de scripting. Em suma, a nossa plataforma pode ser descrita como um sistema que converte informação musical em alterações arbitrárias a um ambiente, que por sua vez influencia uma simulação reativa, produzindo animações. Foi estabelecido um compromisso entre controlo e automação de forma a tornar esta abordagem possível. O controlo provém da capacidade de programar as modificações que ocorrem no sistema, sendo que é utilizada automação de forma a estimar o movimento resultante de tais modificações. Ao fornecer ao utilizador informação musical em tempo real e oferecer-lhe controlo sobre o que nos referimos como "primitivas de animação", como o controlo sobre vento e o crescimento da árvore, consideramos que demos um primeiro passo no que toca à exploração de um novo conceito, com um potencial expressivo aparentemente infinito

A novel lip geometry approach for audio-visual speech recognition

By identifying lip movements and characterizing their associations with speech sounds, the performance of speech recognition systems can be improved, particularly when operating in noisy environments. Various method have been studied by research group around the world to incorporate lip movements into speech recognition in recent years, however exactly how best to incorporate the additional visual information is still not known. This study aims to extend the knowledge of relationships between visual and speech information specifically using lip geometry information due to its robustness to head rotation and the fewer number of features required to represent movement. A new method has been developed to extract lip geometry information, to perform classification and to integrate visual and speech modalities. This thesis makes several contributions. First, this work presents a new method to extract lip geometry features using the combination of a skin colour filter, a border following algorithm and a convex hull approach. The proposed method was found to improve lip shape extraction performance compared to existing approaches. Lip geometry features including height, width, ratio, area, perimeter and various combinations of these features were evaluated to determine which performs best when representing speech in the visual domain. Second, a novel template matching technique able to adapt dynamic differences in the way words are uttered by speakers has been developed, which determines the best fit of an unseen feature signal to those stored in a database template. Third, following on evaluation of integration strategies, a novel method has been developed based on alternative decision fusion strategy, in which the outcome from the visual and speech modality is chosen by measuring the quality of audio based on kurtosis and skewness analysis and driven by white noise confusion. Finally, the performance of the new methods introduced in this work are evaluated using the CUAVE and LUNA-V data corpora under a range of different signal to noise ratio conditions using the NOISEX-92 dataset

Modelling and Animation using Partial Differential Equations. Geometric modelling and computer animation of virtual characters using elliptic partial differential equations.

This work addresses various applications pertaining to the design, modelling and animation of parametric surfaces using elliptic Partial Differential Equations (PDE) which are produced via the PDE method. Compared with traditional surface generation techniques, the PDE method is an effective technique that can represent complex three-dimensional (3D) geometries in terms of a relatively small set of parameters. A PDE-based surface can be produced from a set of pre-configured curves that are used as the boundary conditions to solve a number of PDE. An important advantage of using this method is that most of the information required to define a surface is contained at its boundary. Thus, complex surfaces can be computed using only a small set of design parameters. In order to exploit the advantages of this methodology various applications were developed that vary from the interactive design of aircraft configurations to the animation of facial expressions in a computer-human interaction system that utilizes an artificial intelligence (AI) bot for real time conversation. Additional applications of generating cyclic motions for PDE based human character integrated in a Computer-Aided Design (CAD) package as well as developing techniques to describe a given mesh geometry by a set of boundary conditions, required to evaluate the PDE method, are presented. Each methodology presents a novel approach for interacting with parametric surfaces obtained by the PDE method. This is due to the several advantages this surface generation technique has to offer. Additionally, each application developed in this thesis focuses on a specific target that delivers efficiently various operations in the design, modelling and animation of such surfaces.The project files will not be available online

Adaptive Methods for Point Cloud and Mesh Processing

Point clouds and 3D meshes are widely used in numerous applications ranging from games to virtual reality to autonomous vehicles. This dissertation proposes several approaches for noise removal and calibration of noisy point cloud data and 3D mesh sharpening methods. Order statistic filters have been proven to be very successful in image processing and other domains as well. Different variations of order statistics filters originally proposed for image processing are extended to point cloud filtering in this dissertation. A brand-new adaptive vector median is proposed in this dissertation for removing noise and outliers from noisy point cloud data. The major contributions of this research lie in four aspects: 1) Four order statistic algorithms are extended, and one adaptive filtering method is proposed for the noisy point cloud with improved results such as preserving significant features. These methods are applied to standard models as well as synthetic models, and real scenes, 2) A hardware acceleration of the proposed method using Microsoft parallel pattern library for filtering point clouds is implemented using multicore processors, 3) A new method for aerial LIDAR data filtering is proposed. The objective is to develop a method to enable automatic extraction of ground points from aerial LIDAR data with minimal human intervention, and 4) A novel method for mesh color sharpening using the discrete Laplace-Beltrami operator is proposed. Median and order statistics-based filters are widely used in signal processing and image processing because they can easily remove outlier noise and preserve important features. This dissertation demonstrates a wide range of results with median filter, vector median filter, fuzzy vector median filter, adaptive mean, adaptive median, and adaptive vector median filter on point cloud data. The experiments show that large-scale noise is removed while preserving important features of the point cloud with reasonable computation time. Quantitative criteria (e.g., complexity, Hausdorff distance, and the root mean squared error (RMSE)), as well as qualitative criteria (e.g., the perceived visual quality of the processed point cloud), are employed to assess the performance of the filters in various cases corrupted by different noisy models. The adaptive vector median is further optimized for denoising or ground filtering aerial LIDAR data point cloud. The adaptive vector median is also accelerated on multi-core CPUs using Microsoft Parallel Patterns Library. In addition, this dissertation presents a new method for mesh color sharpening using the discrete Laplace-Beltrami operator, which is an approximation of second order derivatives on irregular 3D meshes. The one-ring neighborhood is utilized to compute the Laplace-Beltrami operator. The color for each vertex is updated by adding the Laplace-Beltrami operator of the vertex color weighted by a factor to its original value. Different discretizations of the Laplace-Beltrami operator have been proposed for geometrical processing of 3D meshes. This work utilizes several discretizations of the Laplace-Beltrami operator for sharpening 3D mesh colors and compares their performance. Experimental results demonstrated the effectiveness of the proposed algorithms

Depth-Assisted Semantic Segmentation, Image Enhancement and Parametric Modeling

This dissertation addresses the problem of employing 3D depth information on solving a number of traditional challenging computer vision/graphics problems. Humans have the abilities of perceiving the depth information in 3D world, which enable humans to reconstruct layouts, recognize objects and understand the geometric space and semantic meanings of the visual world. Therefore it is significant to explore how the 3D depth information can be utilized by computer vision systems to mimic such abilities of humans. This dissertation aims at employing 3D depth information to solve vision/graphics problems in the following aspects: scene understanding, image enhancements and 3D reconstruction and modeling. In addressing scene understanding problem, we present a framework for semantic segmentation and object recognition on urban video sequence only using dense depth maps recovered from the video. Five view-independent 3D features that vary with object class are extracted from dense depth maps and used for segmenting and recognizing different object classes in street scene images. We demonstrate a scene parsing algorithm that uses only dense 3D depth information to outperform using sparse 3D or 2D appearance features. In addressing image enhancement problem, we present a framework to overcome the imperfections of personal photographs of tourist sites using the rich information provided by large-scale internet photo collections (IPCs). By augmenting personal 2D images with 3D information reconstructed from IPCs, we address a number of traditionally challenging image enhancement techniques and achieve high-quality results using simple and robust algorithms. In addressing 3D reconstruction and modeling problem, we focus on parametric modeling of flower petals, the most distinctive part of a plant. The complex structure, severe occlusions and wide variations make the reconstruction of their 3D models a challenging task. We overcome these challenges by combining data driven modeling techniques with domain knowledge from botany. Taking a 3D point cloud of an input flower scanned from a single view, each segmented petal is fitted with a scale-invariant morphable petal shape model, which is constructed from individually scanned 3D exemplar petals. Novel constraints based on botany studies are incorporated into the fitting process for realistically reconstructing occluded regions and maintaining correct 3D spatial relations. The main contribution of the dissertation is in the intelligent usage of 3D depth information on solving traditional challenging vision/graphics problems. By developing some advanced algorithms either automatically or with minimum user interaction, the goal of this dissertation is to demonstrate that computed 3D depth behind the multiple images contains rich information of the visual world and therefore can be intelligently utilized to recognize/ understand semantic meanings of scenes, efficiently enhance and augment single 2D images, and reconstruct high-quality 3D models

Mining a Small Medical Data Set by Integrating the Decision Tree and t-test

[[abstract]]Although several researchers have used statistical methods to prove that aspiration followed by the injection of 95% ethanol left in situ (retention) is an effective treatment for ovarian endometriomas, very few discuss the different conditions that could generate different recovery rates for the patients. Therefore, this study adopts the statistical method and decision tree techniques together to analyze the postoperative status of ovarian endometriosis patients under different conditions. Since our collected data set is small, containing only 212 records, we use all of these data as the training data. Therefore, instead of using a resultant tree to generate rules directly, we use the value of each node as a cut point to generate all possible rules from the tree first. Then, using t-test, we verify the rules to discover some useful description rules after all possible rules from the tree have been generated. Experimental results show that our approach can find some new interesting knowledge about recurrent ovarian endometriomas under different conditions.[[journaltype]]國外[[incitationindex]]EI[[booktype]]紙本[[countrycodes]]FI