Análise de texturas dinâmicas baseada em sistemas complexosdissertation
Аннотация: Dynamic texture analysis has been an area of research increasing and in potential in recent years in computer vision.Dynamic textures are sequences of texture images (i.e.video) that represent dynamic objects.Examples of dynamic textures are: evolution of the colony of bacteria, growth of body tissues, moving escalator, waterfalls, smoke, process of metal corrosion, among others.Although there are researches related to the topic and promising results, most literature methods have limitations.Moreover, in many cases the dynamic textures are the result of complex phenomena, making a characterization task even more challenging.This scenario requires the development of a paradigm of methods based on complexity.The complexity can be understood as a measure of irregularity of the dynamic textures, allowing to measure the structure of the pixels and to quantify the spatial and temporal aspects.In this context, this masters aims to study and develop methods for the characterization of dynamic textures based on methodologies of complexity from the area of complex systems.In particular, two methodologies already used in computer vision problems are considered: complex networks and deterministic walk partially self-repulsive.Based on these methodologies, three methods of characterization of dynamic textures were developed: (i) based on diffusion in networks (ii) based on deterministic walk partially self-repulsive (iii) based on networks generated by deterministic walk partially self-repulsive.The developed methods were applied in problems of nanotechnology and vehicle traffic, presenting potencial results and contribuing to the development of both areas.
Год издания: 2017
Авторы: Lucas C. Ribas
Ключевые слова: Complex Network Analysis Techniques, Complex Systems and Time Series Analysis, Data Visualization and Analytics
Открытый доступ: gold