As advances of information technology, engineering consulting firms have gradually digitalized their documents and line-drawing images. Such digital libraries greatly facilitate document retrievals. However, engineers still face a challenging issue: searches and retrievals of line-drawing images in a digital library. With a small number of line-drawing images in a digital library, engineers can browse thumbnails for locating relevant images. As the number of line-drawing images increases, the manual browsing process is time-consuming and frustrated. In response to the need and importance of supporting efficient and effective retrieval of line-drawing images, this thesis aims to develop a line-drawing image retrieval system. Typically, a line-drawing image within an engineering document is associated with surrounding text for description or illustration purpose. Such surrounding text provides important information for automatically indexing the line-drawing image. With extracted indexes (or keywords), retrieval of line-drawing images can be accomplished using a traditional information retrieval technique. Specifically, in this study, we propose a line-drawing image retrieval system based on surrounding text. We develop four models for defining surrounding text boundaries for line-drawing images. Furthermore, two information retrieval techniques (one with and one without query expansion) are implemented and evaluated. According to our empirical evaluations, the surrounding text boundary model with image caption together with three sentences (preceding, image anchoring, and successive sentences) would result in the best retrieval effectiveness, as measured by recall and precision rates.

This diploma thesis deals with Bryophyta studies as a part of curriculum at primary schools as well as at lower and upper grammar schools. It determines the field of studies and the expected outcomes in the Human and Nature subject matter, it searches for the link between bryophyta and cross-sectional topics. The relation of pupil's key competences to bryophyta is being reflected, too. It compares the subject range of Bryophyta in school books. Furthermore, the thesis sums up the history of botanical illustration in the world as well as in our country, it inquires into basic rules of botanical illustration and line drawing techniques. The contemporary field guides are completed by the means of the research of students' books, popular and specialist literature and internet portals. Based on the theoretical part, this diploma thesis determines the teaching methodology of bryophyta drawing. The list of bryophyta, which are suitable for line drawings and usable as a teaching aid, is based on the practical part of this diploma thesis. 43 author's drawings with uniform measuring scale are attached.

Humans have always used sketches to explain the visual world. It is a simple and straight- forward mean to communicate new ideas and designs. Consequently, as in almost every aspect of our modern life, the relatively recent major developments in computer science have highly contributed to enhancing individual sketching experience. The literature of sketch related research has witnessed seminal advancements and a large body of interest- ing work. Following up with this rich literature, this dissertation provides a holistic study on sketches through three proposed novel models including sketch analysis, transfer, and geometric representation. The first part of the dissertation targets sketch authorship recognition and analysis of sketches. It provides answers to the following questions: Are simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? The proposed stroke authorship recognition approach is a novel method that distinguishes the authorship of 2D digitized drawings. This method converts a drawing into a histogram of stroke attributes that is discriminative of authorship. Extensive classification experiments on a large variety of datasets are conducted to validate the ability of the proposed techniques to distinguish unique authorship of artists and designers. The second part of the dissertation is concerned with sketch style transfer from one free- hand drawing to another. The proposed method exploits techniques from multi-disciplinary areas including geometrical modeling and image processing. It consists of two methods of transfer: stroke-style and brush-style transfer. (1) Stroke-style transfer aims to transfer the style of the input sketch at the stroke level to the style encountered in other sketches by other artists. This is done by modifying all the parametric stroke segments in the input, so as to minimize a global stroke-level distance between the input and target styles. (2) Brush-style transfer, on the other hand, focuses on transferring a unique brush look of a line drawing to the input sketch. In this transfer stage, we use an automatically constructed input brush dictionary to infer which sparse set of input brush elements are used at each location of the input sketch. Then, a one-to-one mapping between input and target brush elements is learned by sparsely encoding the target sketch with the input brush dictionary. The last part of the dissertation targets a geometric representation of sketches, which is vital in enabling automatic sketch analysis, synthesis and manipulation. It is based on utilizing the well known convolutional sparse coding (CSC) model. We observe that CSC is closely related to how line sketches are drawn. This process can be approximated as the sparse spatial localization of a number of typical basic strokes, which in turn can be cast as a non-standard CSC model that forms a line drawing from parametric curves. These curves are learned to optimize the fit between the model and a specific set of line drawings. Each part of the dissertation shows the utility of the proposed methods through a variety of experiments, user studies, and proposed applications.

This thesis proposes machine learning algorithms for processing geometry by example. Each algorithm takes as input a collection of shapes along with exemplar values of target properties related to shape processing tasks. The goal of the algorithms is to output a function that maps from the shape data to the target properties. The learned functions can be applied to novel input shape data in order to synthesize the target properties with style similar to the training examples. Learning such functions is particularly useful for two different types of geometry processing problems. The first type of problems involves learning functions that map to target properties required for shape interpretation and understanding. The second type of problems involves learning functions that map to geometric attributes of animated shapes required for real-time rendering of dynamic scenes. With respect to the first type of problems involving shape interpretation and understanding, I demonstrate learning for shape segmentation and line illustration. For shape segmentation, the algorithms learn functions of shape data in order to perform segmentation and recognition of parts in 3D meshes simultaneously. This is in contrast to existing mesh segmentation methods that attempt segmentation without recognition based only on low-level geometric cues. The proposed method does not require any manual parameter tuning and achieves significant improvements in results over the state-of-the-art. For line illustration, the algorithms learn functions from shape and shading data to hatching properties, given a single exemplar line illustration of a shape. Learning models of such artistic-based properties is extremely challenging, since hatching exhibits significant complexity as a network of overlapping curves of varying orientation, thickness, density, as well as considerable stylistic variation. In contrast to existing algorithms that are hand-tuned or hand-designed from insight and intuition, the proposed technique offers a largely automated and potentially natural workflow for artists. With respect to the second type of problems involving fast computations of geometric attributes in dynamic scenes, I demonstrate algorithms for learning functions of shape animation parameters that specifically aim at taking advantage of the spatial and temporal coherence in the attribute data. As a result, the learned mappings can be evaluated very efficiently during runtime. This is especially useful when traditional geometric computations are too expensive to re-estimate the shape attributes at each frame. I apply such algorithms to efficiently compute curvature and high-order derivatives of animated surfaces. As a result, curvature-dependent tasks, such as line drawing, which could be previously performed only offline for animated scenes, can now be executed in real-time on modern CPU hardware.

This thesis proposes machine learning algorithms for processing geometry by example. Each algorithm takes as input a collection of shapes along with exemplar values of target properties related to shape processing tasks. The goal of the algorithms is to output a function that maps from the shape data to the target properties. The learned functions can be applied to novel input shape data in order to synthesize the target properties with style similar to the training examples. Learning such functions is particularly useful for two different types of geometry processing problems. The first type of problems involves learning functions that map to target properties required for shape interpretation and understanding. The second type of problems involves learning functions that map to geometric attributes of animated shapes required for real-time rendering of dynamic scenes. With respect to the first type of problems involving shape interpretation and understanding, I demonstrate learning for shape segmentation and line illustration. For shape segmentation, the algorithms learn functions of shape data in order to perform segmentation and recognition of parts in 3D meshes simultaneously. This is in contrast to existing mesh segmentation methods that attempt segmentation without recognition based only on low-level geometric cues. The proposed method does not require any manual parameter tuning and achieves significant improvements in results over the state-of-the-art. For line illustration, the algorithms learn functions from shape and shading data to hatching properties, given a single exemplar line illustration of a shape. Learning models of such artistic-based properties is extremely challenging, since hatching exhibits significant complexity as a network of overlapping curves of varying orientation, thickness, density, as well as considerable stylistic variation. In contrast to existing algorithms that are hand-tuned or hand-designed from insight and intuition, the proposed technique offers a largely automated and potentially natural workflow for artists. With respect to the second type of problems involving fast computations of geometric attributes in dynamic scenes, I demonstrate algorithms for learning functions of shape animation parameters that specifically aim at taking advantage of the spatial and temporal coherence in the attribute data. As a result, the learned mappings can be evaluated very efficiently during runtime. This is especially useful when traditional geometric computations are too expensive to re-estimate the shape attributes at each frame. I apply such algorithms to efficiently compute curvature and high-order derivatives of animated surfaces. As a result, curvature-dependent tasks, such as line drawing, which could be previously performed only offline for animated scenes, can now be executed in real-time on modern CPU hardware.

This paper is intended to serve as a supporting document for the exhibition "No Peace" that was held at the Artery Gallery, 158 King St. W, Kitchener, ON, Canada, March 28 - April 18, 2009. This drawing installation presents the emotional restlessness of an immigrant who lives in a peaceful place but at the same time is tormented by the ongoing war in his homeland. The drawings make use of the vocabulary of abstraction while presenting the physical process of a repetitive line-based action. The work does not illustrate a political narrative but reflect on recent global issues by using the personal language of art. The No Peace installation combines drawing with video, animation, and performance in the hope of gaining a more communicative interaction with the viewer.

This paper is intended to serve as a supporting document for the exhibition "No Peace" that was held at the Artery Gallery, 158 King St. W, Kitchener, ON, Canada, March 28 - April 18, 2009. This drawing installation presents the emotional restlessness of an immigrant who lives in a peaceful place but at the same time is tormented by the ongoing war in his homeland. The drawings make use of the vocabulary of abstraction while presenting the physical process of a repetitive line-based action. The work does not illustrate a political narrative but reflect on recent global issues by using the personal language of art. The No Peace installation combines drawing with video, animation, and performance in the hope of gaining a more communicative interaction with the viewer.

Cette thèse prend pour cadre la synthèse par l'exemple et l'édition de contenu graphique en infographie et propose une réflexion sur les possibles sources d'information utiles à ces fins. Contrairement aux techniques "procédurales", l'approche par l'exemple se distingue par sa grande simplicité d'utilisation : reviennent en effet à l'algorithme de synthèse l'identification, analyse et reproduction des éléments caractéristiques des exemples fournis en entrée par l'utilisateur. Ce mode de création de même que les techniques approfondies d'édition ont grandement contribué à la facilitation de la production à grande échelle de contenus graphiques convaincants et ainsi participé à l'adoption par la communauté des artistes des outils proposés par le support numérique. Mais pour être ainsi exploitées, celles-ci doivent également être hautement contrôlables tout en évitant l'écueil de n'être que le simple prolongement de la main de l'artiste. Nous explorons ici cette thématique dans le cadre de la création de rendus dits expressifs et étudions les interactions (collaboratives ou concurrentielles) entre les différentes sources d'information au cœur de ce processus. Ces dernières sont à notre sens au nombre de trois : l'analyse automatique des données d'entrée avant rendu ou traitement ; l'utilisation de modèles a priori en vue de leur compréhension ; et enfin le contrôle explicite par l'utilisateur. En les combinant au plus juste, nous proposons des techniques nouvelles dans divers domaines de la synthèse en rendu expressif. Au delà du réalisme photographique, le rendu expressif se caractérise par sa poursuite de critères plus difficilement quantifiables tels la facilité de compréhension ou le caractère artistique de ses résultats. La subjectivité de tels objectifs nous force donc ici plus qu'ailleurs à estimer avec soin les sources d'information à privilégier, le niveau d'implication à accorder à l'utilisateur (sans que ce choix ne s'opère au détriment de la qualité théorique de la méthode), ainsi que le possible recours à des modèles d'analyse (sans en compromettre la généralité). Trois principales instances de synthèse sont ici détaillés : la génération de textures, la désaturation d'images, et la représentation de maillages par le dessin au trait. La grande variété des données d'entrée (textures matricielles ou vectorielles, images complexes, géométries 3d), des modalités de synthèse (imitation, conversion, représentation alternative) et d'objectifs (reproduction de la signature visuelle d'une texture, restitution crédible de contrastes chromatiques, génération de dessins conformes au style de l'utilisateur) permettent l'examen de divers équilibres entre ces sources d'information et l'exploration de degrés plus ou moins élevés d'interaction avec l'utilisateur. / This thesis focuses on example-based synthesis and editing in Computer Graphics and reflects on the possible sources of information necessary for such goals. Unlike "procedural" techniques, synthesis by example stands out thanks to its extreme ease-of-use : indeed, tasks such as identification, analysis and reproduction of the distinguishing features of the user-provided examples are left to the method itself. Such approaches, along with today's intricate editing methods have greatly favored the production of compelling graphical content at a wide scale, and henceforth facilitated the adoption of computer-assisted tools by artists. But in order to meet with success, they also have to be highly controllable without being a mere extension of the artist's hand. We explore here such concerns in the context of expressive rendering and study the interactions, may they be collaborative or competitive, between the different sources of information at the core of such processes. In our opinion, there are three main sources of information: the automatic analysis of the inputs before processing; the use of prior knowledge through predetermined models; and users' explicit intervention. Through a clever combination of these sources, we propose new expressive synthesis techniques which satisfy the aforementioned usability. More than photographic realism, expressive rendering strives for the fulfillment of less easily quantifiable goals such as the intelligibility or the aesthetic value of its results. The subjectivity behind the assessment of such criteria thus forces us to attach much importance to the careful choice of the source of information to favor; the required amount of user intervention (without being detrimental to the method's theoretical value); and the possible resort to prior models (without endangering its generality). Three main synthesis instances are studied in this document: texture generation, image de-colorization, and artistic line rendering. The great disparity of inputs (raster and vector textures, complex images, 3d meshes), terms of synthesis (imitation, conversion, depiction) and objectives (preservation of a texture's visual signature, plausible restitution of chromatic contrasts, creation of drawings in accordance with users' styles) gives rise to distinct balances between those sources of information and requires the consideration of various modes of user interaction.