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Pre-visualisation is an important tool for planning films during the pre-production phase of filmmaking. Existing pre-visualisation authoring tools do not effectively support the user in authoring pre-visualisations without impairing software usability. These tools require the user to either have programming skills, be experienced in modelling and animation, or use drag-and-drop style interfaces. These interaction methods do not intuitively fit with pre-production activities such as floor planning and storyboarding, and existing tools that apply a storyboarding metaphor do not automatically interpret user sketches. The goal of this research was to investigate how sketch-based user interfaces and methods from computer vision could be used for supporting pre-visualisation authoring using a storyboarding approach. The requirements for such a sketch-based storyboarding tool were determined from literature and an interview with Triggerfish Animation Studios. A framework was developed to support sketch-based pre-visualisation authoring using a storyboarding approach. Algorithms for describing user sketches, recognising objects and performing pose estimation were designed to automatically interpret user sketches. A proof of concept prototype implementation of this framework was evaluated in order to assess its usability benefit. It was found that the participants could author pre-visualisations effectively, efficiently and easily. The results of the usability evaluation also showed that the participants were satisfied with the overall design and usability of the prototype tool. The positive and negative findings of the evaluation were interpreted and combined with existing heuristics in order to create a set of guidelines for designing similar sketch-based pre-visualisation authoring tools that apply the storyboarding approach. The successful implementation of the proof of concept prototype tool provides practical evidence of the feasibility of sketch-based pre-visualisation authoring. The positive results from the usability evaluation established that sketch-based interfacing techniques can be used effectively with a storyboarding approach for authoring pre-visualisations without impairing software usability.

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This dissertation is concerned with the representation of visual knowledge. Image features often have many different local interpretations. As a result, visual interpretations are often ambiguous and hypothetical. In many model-based vision systems the problem of representing ambiguous and hypothetical interpretations is not very specifically addressed. Generally, specialization hierarchies are used to suppress a potential explosion in local interpretations. Such a solution has problems, as many local interpretations cannot be represented by a single hierarchy. As well, ambiguous and hypothetical interpretations tend to be represented along more than one knowledge representation dimension limiting modularity in representation and control. In this dissertation a better solution is proposed. Classes of objects which have local features with similar appearance in the image are represented by discrimination graphs. Such graphs are directed and acyclic. Their leaves represent classes of elementary objects. All other nodes represent abstract (and sometimes unnatural) classes of objects, which intensionally represent the set of elementary object classes that descend from them. Rather than interpreting each image feature as an elementary object, we use the abstract class that represents the complete set of possible (elementary) objects. Following the principle of least commitment, the interpretation of each image feature is repeatedly forced into more restrictive classes as the context for the image feature is expanded, until the image no longer provides subclassification information. This approach is called discrimination vision, and it has several attractive features. First, hypothetical and ambiguous interpretations can be represented along one knowledge representation dimension. Second, the number of hypotheses represented for a single image feature can be kept small. Third, in an interpretation graph competing hypotheses can be represented in the domain of a single variable. This often eliminates the need for restructuring the graph when a hypothesis is invalidated. Fourth, the problem of resolving ambiguity can be treated as a constraint satisfaction problem which is a well researched problem in Computational Vision. Our system has been implemented as Mapsee-3, a program for interpreting sketch maps. A hierarchical arc consistency algorithm has been used to deal with the inherently hierarchical discrimination graphs. Experimental data show that, for the domain implemented, this algorithm is more efficient than standard arc consistency algorithms. / Science, Faculty of / Computer Science, Department of / Graduate

This thesis describes and compares several methods for producing bilevel patterns to simulate grey level values for use in polygon regions as generated for computer graphics. Random distribution, ordered dither, and error diffusion methods are shown to be visually inferior for many grey levels to the proposed maxmin algorithm for producing patterns for polygon area filling procedures. Through even spatial arrangement of the pixels and taking into consideration the edges of the pattern, the number of artifacts is decreased and the accuracy in small subregions of the pattern is improved, especially at low grey levels where most pattern generators degrade. At these lower levels, the maxmin algorithm can produce pleasing patterns if given sufficient flexibility through enlarged grid sizes. At higher grey levels, the proximity of pixels does not leave sufficient room to eliminate all artifacts, but by varying the criteria of the algorithm, the patterns still appear more pleasing than other methods. / Science, Faculty of / Computer Science, Department of / Graduate

The design and implementation of an interactive graphics system for graph manipulation are discussed. The activation fcr such a system is examined, and the relevant literature is described and evaluated. A number of ways to improve and extend the system are presented. The system provides the basic graph drawing operations cf adding, deleting, labeling, and changing both vertices and edges. Also included are a number of graph manipulation operations which, among ether things, allow a user to subdivide edges, associate vertices, reverse the direction cf arcs, move vertices about the screen, cr even move whole graphs about the sc teen. A facility is provided whereby the screen can te divided into as many as four regions, thus allowing users tc display more than one graph at a time. Graphs can be saved on disk and later restored. The image on the graphics screen can te easily plotted tc obtain a hard copy of graphs. A few routines which perform graph-theoretic operations have teen implemented. Among these are a routine for finding the minimum and maximum degrees of a graph, and a routine fcr finding the blocks, cutnodes, and bridges cf a graph. Moreover, the system is designed to allow users to add their own routines. / Science, Faculty of / Computer Science, Department of / Graduate

This thesis describes Polygon Filling System, an interactive graphics system, which fills user defined areas on a raster scan graphics display device. The areas may be concave or convex and may be nested within each other. Issues related to the underlying grid model, hexagonal or square tesselation, are discussed. A formal approach to polygon filling is compared to a heuristic domain dependent approach. Connectivity problems arise in processing boundaries. Two user rules are defined. Adherence to these rules ensures correct processing of data. These rules are appropriate for cartographic and remote sensing applications. The implementation of the system and its key data structures are described. / Science, Faculty of / Computer Science, Department of / Graduate

Time-series data draw extensive attention from many research domains, such as financial and biomedical engineering. Researchers often face the difficultly of visualizing multiple time-series data simultaneously. The predominant techniques suffer from visual clutter either due to over-plotting or an overwhelming number of small graphs that carries a high cognitive load. This research study proposes a Colored slope, a combination of Tufte's slope graph and time-series heatmap, to visualize multiple time-series data at once, balancing scalability and accuracy. Colored slope inherits the complementary advantages from each method, regarding visualizing temporal changes within a period and identifying precise values. The efficacy, effectiveness, and graphical perception of the Colored slope on visualizing multiple time-series data with publicly accessible stock data were evaluated and compared it to popular time-series visualizations, including line graphs, time-series heatmap, and small multiple spark area graphs. Analyzing the experimental data, this study concludes that Colored slope contributes to (1) allowing users to identify the extreme values (maximum and minimum), co-variability, the general trend of the data, and rate of change effectively for an optimally large number of visual marks(time-series data); (2) capable of display more instances of time-series data with a less visual clutter problem. Finally, several possible applications and limitations with the Colored slope are demonstrated.