3D Reconstruction for Optimal Representation of Surroundings in Automotive HMIs, Based on Fisheye Multi-Camera Systems

The aim of this thesis is the development of new concepts for environmental 3D reconstruction in automotive surround-view systems where information of the surroundings of a vehicle is displayed to a driver for assistance in parking and low-speed manouvering. The proposed driving assistance system represents a multi-disciplinary challenge combining techniques from both computer vision and computer graphics. This work comprises all necessary steps, namely sensor setup and image acquisition up to 3D rendering in order to provide a comprehensive visualization for the driver. Visual information is acquired by means of standard surround-view cameras with fish eye optics covering large fields of view around the ego vehicle. Stereo vision techniques are applied to these cameras in order to recover 3D information that is finally used as input for the image-based rendering. New camera setups are proposed that improve the 3D reconstruction around the whole vehicle, attending to different criteria. Prototypic realization was carried out that shows a qualitative measure of the results achieved and prove the feasibility of the proposed concept

Coprocessador baseado em FPGA para a visão de um robô futebolista

Mestrado em Engenharia de Computadores e TelemáticaA área da robótica encontra-se em constante evolução, assumindo, nos dias de hoje, uma elevada importância nas mais diversas áreas. Uma grande parte das soluções desenvolvidas neste campo tem como requisito o reconhecimento visual do meio envolvente, possibilitando ao sistema robótico reconhecer determinados objetos ou formas, e/ou tomar decisões e reagir perante determinadas situações. Por outro lado, a visão computacional assume-se como uma ciência de ampla aplicação, o que implica a necessidade de optar pelo sistema de visão mais adequado a cada realidade. A competição RoboCup surge como uma iniciativa internacional com o objetivo principal de promover a investigação e desenvolvimento da inteligência artificial, robótica e demais áreas relacionadas. Embora existam outras, as principais competições presentes nesta iniciativa envolvem a organização de encontros anuais, onde equipas de robótica de todo o mundo jogam futebol entre si. Estas competições encontram-se agrupadas em determinadas categorias, sendo que a mais relevante no âmbito deste projeto é a liga de robôs médios (RoboCup MSL), onde a equipa CAMBADA representa a Universidade de Aveiro. Neste tipo de competição, o sistema de visão assume uma importância vital, uma vez que a perceção da bola, das linhas brancas e obstáculos, bem como o seu consequente processamento, de forma rápida e eficiente, são uma mais-valia para a tomada de decisão de um robô, face a uma determinada situação. No entanto, os algoritmos associados ao processamento de imagem são tipicamente muito exigentes, quer em termos de recursos, quer em termos de processamento, podendo o tempo necessário ao seu processamento comprometer uma resposta eficaz e, por conseguinte, todo o sistema. Esta dissertação resulta da necessidade de melhorar continuamente a prestação desta equipa nas competições em que participa, através do desenvolvimento e implementação de um coprocessador baseado em FPGA, o que se apresenta como uma mais-valia, dado permitir a redução do peso computacional da visão por computador da CAMBADA. Este coprocessador será responsável pela execução de uma parte dos algoritmos de visão, nomeadamente, segmentação de cor, compressão de imagem e deteção de bolhas de cor, baseando-se em diversos núcleos de processamento, quer genéricos, quer especializados, explorando, desta forma, o paralelismo normalmente disponível neste tipo de algoritmos. Este sistema possui ainda capacidade de adquirir de forma autónoma as imagens, processando-as individualmente e disponibilizando os resultados ao computador principal. O presente projeto pretende demonstrar a aplicabilidade e a supremacia da implementação de tarefas computacionalmente intensivas em hardware reconfigurável.The eld of robotics is evolving, assuming, nowadays, a high importance in several areas. A large part of the solutions developed in this eld have as a requirement, the visual recognition of the surrounding environment, allowing the robotic system to recognize certain objects or shapes, and/or make decisions and react to certain situations. Moreover, computer vision is assumed as a science of wide application, which implies the need to choose the most appropriate vision system to each situation. The RoboCup competition emerges as an international initiative with the main objective to promote research and development of arti cial intelligence, robotics and other related areas. Although there are other competitions, major competitions present in this initiative involve the organization of annual meetings, where robotics teams from around the world play soccer between them. These competitions are grouped into certain categories, where the most relevant in the context of this project is the Middle Size League of robots (RoboCup MSL), where CAMBADA team represents the University of Aveiro. In this type of competition, the vision system is of vital importance, since the perception of the ball, the white lines or obstacles, as well as their subsequent processing quickly and e ciently, are an added value for decision making of a robot to a speci c situation. However, the algorithms associated with the image processing are typically very demanding, both in terms of resources, as in terms of processing, which enables the overall processing time can compromise an e ective answer and therefore, the whole system. This work stems from the need to continuously improve the performance of this team in the competitions in which it participates, through the development and implementation of an FPGA-based coprocessor, which is presented as an advantage, since it allows a weight reduction of vision computation in each computer of CAMBADA. This coprocessor is responsible for executing a portion of vision algorithms, namely, color segmentation, image compression and detection of color bubbles, based on various processing cores, either generic or specialized, thus exploiting the parallelism usually available in this type of algorithms. This system also has the ability to autonomously acquire the images, processing them individually and providing the results to the main computer. This project aims to demonstrate the applicability and supremacy of the implementation of computationally intensive tasks on recon gurable hardware

Sensor Network Based Collision-Free Navigation and Map Building for Mobile Robots

Safe robot navigation is a fundamental research field for autonomous robots including ground mobile robots and flying robots. The primary objective of a safe robot navigation algorithm is to guide an autonomous robot from its initial position to a target or along a desired path with obstacle avoidance. With the development of information technology and sensor technology, the implementations combining robotics with sensor network are focused on in the recent researches. One of the relevant implementations is the sensor network based robot navigation. Moreover, another important navigation problem of robotics is safe area search and map building. In this report, a global collision-free path planning algorithm for ground mobile robots in dynamic environments is presented firstly. Considering the advantages of sensor network, the presented path planning algorithm is developed to a sensor network based navigation algorithm for ground mobile robots. The 2D range finder sensor network is used in the presented method to detect static and dynamic obstacles. The sensor network can guide each ground mobile robot in the detected safe area to the target. Furthermore, the presented navigation algorithm is extended into 3D environments. With the measurements of the sensor network, any flying robot in the workspace is navigated by the presented algorithm from the initial position to the target. Moreover, in this report, another navigation problem, safe area search and map building for ground mobile robot, is studied and two algorithms are presented. In the first presented method, we consider a ground mobile robot equipped with a 2D range finder sensor searching a bounded 2D area without any collision and building a complete 2D map of the area. Furthermore, the first presented map building algorithm is extended to another algorithm for 3D map building

Connected Attribute Filtering Based on Contour Smoothness

A new attribute measuring the contour smoothness of 2-D objects is presented in the context of morphological attribute filtering. The attribute is based on the ratio of the circularity and non-compactness, and has a maximum of 1 for a perfect circle. It decreases as the object boundary becomes irregular. Computation on hierarchical image representation structures relies on five auxiliary data members and is rapid. Contour smoothness is a suitable descriptor for detecting and discriminating man-made structures from other image features. An example is demonstrated on a very-high-resolution satellite image using connected pattern spectra and the switchboard platform

Hierarchical Variance Reduction Techniques for Monte Carlo Rendering

Ever since the first three-dimensional computer graphics appeared half a century ago, the goal has been to model and simulate how light interacts with materials and objects to form an image. The ultimate goal is photorealistic rendering, where the created images reach a level of accuracy that makes them indistinguishable from photographs of the real world. There are many applications ñ visualization of products and architectural designs yet to be built, special effects, computer-generated films, virtual reality, and video games, to name a few. However, the problem has proven tremendously complex; the illumination at any point is described by a recursive integral to which a closed-form solution seldom exists. Instead, computer simulation and Monte Carlo methods are commonly used to statistically estimate the result. This introduces undesirable noise, or variance, and a large body of research has been devoted to finding ways to reduce the variance. I continue along this line of research, and present several novel techniques for variance reduction in Monte Carlo rendering, as well as a few related tools. The research in this dissertation focuses on using importance sampling to pick a small set of well-distributed point samples. As the primary contribution, I have developed the first methods to explicitly draw samples from the product of distant high-frequency lighting and complex reflectance functions. By sampling the product, low noise results can be achieved using a very small number of samples, which is important to minimize the rendering times. Several different hierarchical representations are explored to allow efficient product sampling. In the first publication, the key idea is to work in a compressed wavelet basis, which allows fast evaluation of the product. Many of the initial restrictions of this technique were removed in follow-up work, allowing higher-resolution uncompressed lighting and avoiding precomputation of reflectance functions. My second main contribution is to present one of the first techniques to take the triple product of lighting, visibility and reflectance into account to further reduce the variance in Monte Carlo rendering. For this purpose, control variates are combined with importance sampling to solve the problem in a novel way. A large part of the technique also focuses on analysis and approximation of the visibility function. To further refine the above techniques, several useful tools are introduced. These include a fast, low-distortion map to represent (hemi)spherical functions, a method to create high-quality quasi-random points, and an optimizing compiler for analyzing shaders using interval arithmetic. The latter automatically extracts bounds for importance sampling of arbitrary shaders, as opposed to using a priori known reflectance functions. In summary, the work presented here takes the field of computer graphics one step further towards making photorealistic rendering practical for a wide range of uses. By introducing several novel Monte Carlo methods, more sophisticated lighting and materials can be used without increasing the computation times. The research is aimed at domain-specific solutions to the rendering problem, but I believe that much of the new theory is applicable in other parts of computer graphics, as well as in other fields

Proceedings of the International Workshop on Medical Ultrasound Tomography: 1.- 3. Nov. 2017, Speyer, Germany

Ultrasound Tomography is an emerging technology for medical imaging that is quickly approaching its clinical utility. Research groups around the globe are engaged in research spanning from theory to practical applications. The International Workshop on Medical Ultrasound Tomography (1.-3. November 2017, Speyer, Germany) brought together scientists to exchange their knowledge and discuss new ideas and results in order to boost the research in Ultrasound Tomography