Objectives. The goal in radiotherapy is to deliver adequate radiation to the tumor volume while limiting damage to the surrounding healthy tissue. However, this goal is challenged by respiratory-induced motion. The objective of this work was to identify whether motion in electronic portal images can be tracked with an optical flow algorithm and whether a neural network can predict tumor motion. Methods. A multi-resolution optical flow algorithm that incorporates weighting based on the differences between image frames was used to automatically sample the vectors corresponding to the motion. The global motion was obtained by computing the average weighted mean from the set of vectors. The algorithm was evaluated using tumor trajectories taken from seven lung cancer patients, a 3D printed patient tumor and a virtual dynamic multi-leaf collimator (DMLC) system. The feasibility of detecting and tracking motion at the field edge was examined with a proof-of-concept implementation that included (1) an algorithm that detected local motion, and (2) a control algorithm that adapted the virtual MLC. To compensate for system latency, a generalized neural network, using both offline (treatment planning data) and online (during treatment delivery) learning, was implemented for tumor motion prediction. Results and Conclusions. The algorithm tracked the global motion of the target with an accuracy of around 0.5 mm. While the accuracy is similar to other methods, this approach does not require manual delineation of the target and can, therefore, provide real-time autonomous motion estimation during treatment. Motion at the treatment field edge was tracked with an accuracy of -0.4 ± 0.3 mm. This proof-of-concept simulation demonstrated that it is possible to adapt MLC leaves based on the motion detected at the field edges. Unplanned intrusions of external organs-at-risk could be shielded. A generalized network with a prediction error of 0.59 mm, and a shorter initial learning period (compared to previous studies) was achieved. This network may be used as a plug-and-play predictor in which tumor position could be predicted at the start of treatment and the need for pretreatment data and optimization for individual patients may be avoided. / February 2017

O cálculo dos vetores de movimento é utilizado em vários processos na área de visão computacional. Problemas como estabelecer rotas de colisão e movimentação da câmera (egomotion) utilizam os vetores como entrada de algoritmos complexos e que demandam muitos recursos computacionais e consequentemente um consumo maior de energia. O fluxo ótico é uma aproximação do campo gerado pelos vetores de movimento. Porém, para aplicações móveis e de baixo consumo de energia se torna inviável o uso de computadores de uso geral. Um sistema embarcado é definido como um computador desenvolvido com um propósito específico referente à aplicação na qual está inserido. O objetivo principal deste trabalho foi elaborar um módulo em sistema embarcado que realiza o cálculo do fluxo ótico. Foi elaborado um co-projeto de hardware e software dedicado e implementados em FPGAs Cyclone II e Stratix IV para a prototipação do sistema. Desta forma, a implementação de um projeto que auxilia a detecção e medição do movimento é importante não só como aplicação isolada, mas para servir de base no desenvolvimento de outras aplicações como tracking, compressão de vídeos, predição de colisão, etc / The motion vectors calculation is used in many processes in the area of computer vision. Problems such as establishing collision routes and the movement of the camera (egomotion) use this vectors as input for complexes algorithms that require many computational and energy resources. The optical flow is an approximation of the field generated by the motion vectors. However, for mobile, low power consumption applications becomes infeasible to use general-purpose computers. An embedded system is defined as a computer designed with a specific purpose related to the application in which it is inserted. The main objective of this work is to implement a hardware and software co-design to assist the optical flow field calculation using the CycloneII and Stratix IV FPGAs. Sad that, it is easily to see that the implementation of a project to help the detection and measurement of the movement can be the base to the development of others applications like tracking, video compression and collision detection

[pt] Muitos sistemas biológicos utilizam visão como forma primária de sensoriamento. Ao longo de milhões de anos de evolução,as diferentes espécies vêm demonstrando o potencial associado à capacidade de visão.A partir da década de 60,foram iniciados os primeiros estudos no sentido de proporcionar às máquinas esta forma de sensoriamento. A esta nova forma de sensoriamento dá-se o nome de Visão Computacional. Em Visão Computacional,muitos casos requerem a determinação de um campo vetorial que descreva os deslocamentos ocorridos entre dois quadros consecutivos de uma sequência genérica de vídeo.A este campo vetorial dá-se o nome de Optical Flow(Fluxo Ótico). A determinação do Optical Flow é ainda um problema sem solução.No presente trabalho,propõ-se um novo estimador estatístico para a determinação do Fluxo Ótico. Este estimador possui complexidade O(n) e associa um grau de confiabilidade a cada estimativa realizada.É aplicável a qualquer sinal digital(não apenas imagens ou vídeo, mas também a som,volume,etc) e vem demonstrando resultados muito promissores. / [en] Many biological systems make use of vision as its primary sensory mechanism. During million years,different species have been showing the great potencial associated with vison.From the early sixties onwards,studies have been done to provide machines with this important sense.The research area involved in this task is called Computer Vision. In Computer Visiom there are many situations where it is necessary to evaluate a vector field which describes existing displacements between two consecutive frames of a generic video sequence.This vector field is called Optical Flow. The Optical Flow determination is still a problem with unknown solution.This work proposes a new statistic algorithm to estimate the Optical Flow.The proposed algorithm has O(n) complexity and associates a degree of rebeliabity to each estimation. The algorithm can be applied to any digital signal(not only images or videos,but also sound,volume etc)and is achieving promising results.

O problema de contagem de pessoas em uma determinada região é de grande importância, e tem várias aplicações, tais como: planejamento dos serviços fornecidos por cinemas, shoppings centers, companhias de ônibus, assim como para o monitoramento do tráfego de pedestres em áreas urbanas. A necessidade de se conceber sistemas confiáveis capazes de contabilizar, em tempo real, o número de pessoas circulando em uma determinada região tem sido evidenciado por essas aplicações. Este trabalho apresenta um sistema de baixo custo para a estimação do fluxo multidirecional de pedestres, em ambientes abertos e não restritos, baseado na seqüência de imagens digitais, capturadas por uma única câmera vídeo tipo WEBCAM. A câmera é colocada na vertical do espaço a ser monitorado e conectada a um PC através da porta USB. A metodologia tem como base o trabalho desenvolvido por Pádua (2002) e utiliza o algoritmo proposto em Lucas e Kanade (1981) que computa o fluxo óptico das imagens capturadas pela câmera. Uma análise espaço-temporal desse fluxo é realizada para determinar o fluxo multidirecional dos pedestres. / The problem in counting people in restricted area is of great importance in planning the services offered by cinemas, malls and bus companies and also for controlling pedestrians traffic in urban areas. These applications have evinced the need for developing reliable real time systems capable of counting pedestrians in regions of interest. This work presents a low cost system for estimating the multidirectional flow of pedestrians in open areas and non-restricted areas. This system has only one WEBCAM placed in a vertical position in the area to be monitored. This camera is connected to the PC computer system through the USB port. The methodology is based in the work developed by Pádua (2002) and in the algorithm proposed by Lucas e Kanade (1981) that computerizes the optical flow of the images acquired by the stationary camera. The multidirectional flow is estimated by the temporal-space analysis of this optical flow

Algoritmos de detecção de movimento em seqüências de imagens devem satisfazer os requisitos de precisão, robustez e velocidade de processamento. A forma de combinar estes três itens depende do desenvolvimento do algoritmo e da aplicação a que se destina, sem que os itens de robustez e precisão sejam comprometidos. Neste trabalho investigamos técnicas para detecção do movimento que satisfazem tais requisitos. A técnica escolhida para detecção de movimento foi a do fluxo Ótico (FO) devido as suas características de precisão nos resultados. Como esta técnica exige elevado esforço computacional, propõe-se nesta tese uma metodologia que aplica as equações de fluxo ótico em reduzidas áreas da imagem processada. Estas áreas são selecionadas utilizando algumas técnicas de pré-processamento que identificam regiões da imagem com maior probabilidade de movimento presente. Posteriormente a esta identificação são aplicadas as equações de FO nas regiões de interesse. Para avaliação e validação do método proposto, comparam-se os diagramas de agulhas resultantes das áreas reduzidas aos diagramas resultantes de toda a imagem mediante critérios estatísticos e de tempo de processamento envolvido. Os algoritmos são testados utilizando imagens sintéticas e imagens reais. / Algorithms for motion detection in image sequences must satisfy the following requirements: accuracy, robustness and speed. The way that accuracy, robustness and speed are combined depends on the algorithm development and on the application. In this work, it has investigated motion detection techniques that satisfy the mentioned requirements. The Optical Flow technique was chosen for the motion detection due to its good performance in the results. As the Optical Flow requires intensive computational load, we propose in this thesis a methodology where Optical Flow Equations are applied in specific areas of the processed image. These areas were selected using pre-processing techniques that identify regions of image with larger motion probability. After the motion areas identification, Optical Flow Equations are applied to the regions of interest. To assess and validate the proposed method, the needle diagrams obtained in the reduced areas are compared with the ones obtained from the whole image according to statistical criteria and processing time. The proposed algorithms have been tested in synthetic and real images.

We investigate some problems commonly found when dealing with stereo images. Working within the context of visual effects for films, we explore software solutions to issues arising with stereo images captured on-set. These images originate from a wide variety of hardware which may or may not provide additional data support for post-production needs. Generic software solutions are thus greatly to be preferred. This dissertation documents contributions in the following three areas. Each project was undertaken at Double Negative and investigated with the aim of improving the post-production pipeline for 3D films. Colour matching is the process whereby the colours of one view from a stereo pair are matched with those of the other view. This process is necessary due to the fact that slight differences in hardware and viewing angle can result in some surprisingly large colour discrepancies. Chapter 3 presents a novel approach to colour matching between stereo pairs of images, with a new tool for visual effects artists given in section 6.2.Vertical alignment of stereo images is key to providing a comfortable experience for the viewer, yet we are rarely presented with perfectly aligned footage from the outset. In chapter 4 we discuss the importance of correcting misalignments for both the final audience and the artists working on these images. We provide a tool for correcting misalignments in section 6.3.Disparity maps are used in many areas of post-production, and so in chapter 5 we investigate ways in which disparity map generation can be improved for the benefit of many existing tools at Double Negative. In addition, we povide an extensive exploration of the requirements of 3D films in order to make them presentable in the cinema. Through these projects, we have provided improvements to the stereo workflow and shown that academic research is a necessary component of developing tools for the visual effects pipeline. We have provided new algorithms to improve the 3D experience for moviegoers, as well as artists, and conclude by discussing the future work that will provide further gains in the field.

FundaÃÃo Cearense de Apoio ao Desenvolvimento Cientifico e TecnolÃgico / CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / A diminuiÃÃo dos custos de hardware associado ao aumento da capacidade de processamento dos dispositivos portÃteis tem causado um crescimento muito acelerado do mercado consumidor no Brasil e no mundo, de maneira que estes dispositivos tornaram-se uma parte indispensÃvel no nosso cotidiano. Contudo, o crescente fator de miniaturizaÃÃo de componentes gerou problemas em relaÃÃo à interaÃÃo eficiente com perifÃricos de entrada e saÃda tradicionais, como os cursores e o teclado. Assim, para evitar custos adicionais, uma alternativa à utilizar componentes jà existentes no dispositivo, como sua cÃmera integrada. Neste contexto, o objetivo geral desta tese à o desenvolvimento de um novo algoritmo para a interaÃÃo humano-dispositivo portÃtil multiplataforma baseado em fluxo Ãptico. Embora o fluxo Ãptico de Horn (1981) ser conhecido por ser um algoritmo de extrema complexidade computacional, nesta tese à proposto um conjunto de adaptaÃÃes neste algoritmo para tornar possÃvel seu processamento em tempo real em dispositivos portÃteis. O algoritmo proposto à desenvolvido em C ANSI e embarcado em dispositivos com sistemas operacionais Qualcomm REX, Symbian e Android. O algoritmo implementado à comparado com mÃtodos presentes na literatura especializada para detecÃÃo de movimentos atravÃs de simulaÃÃes computacionais e testes de usabilidade. Os resultados mostram que o algoritmo proposto possui um baixo esforÃo computacional associado a uma efetiva detecÃÃo de movimentos, mostrando que à possÃvel o uso do mÃtodo de Fluxo Ãptico como sensor para interaÃÃo em sistemas embarcados. AlÃm disto, atravÃs da metodologia de implementaÃÃo proposta nesta tese, à possÃvel utilizar as funcionalidades desenvolvidas em diversos tipos de sistemas operacionais. / The decrease in hardware costs associated with improvement of processing power of embedded devices has caused a rapid growth of the consumer market, which make these devices an indispensable part of our daily life. However, the miniaturization of these components leads to problems in the usability of mobile devices, especially with traditional input interfaces, such as the cursors and keyboard. One solution to avoid this kind of problem without increase production cost of these devices is use resources available, like the embedded camera. Following this idea, the objective of this thesis is the development of a new multi-platform human-handheld interaction algorithm based in optical flow. Although the traditional optical flow algorithms have high computational effort, in this thesis, adaptations and optimizations of this algorithm are proposed to overcome hardware limitations of embedded systems. The proposed algorithm is implemented in ANSI C and is embedded at devices with Android, Rex and Symbian OS. The implemented algorithm is compared with traditional motion detection algorithm through computational simulations and usability tests. The results shown that the proposed algorithm associates a low computational effort associated with effective motion detection. So it is possible to use the optical flow as sensor to interact with handheld devices. Furthermore, through the implementation methodology of this thesis, is possible use the developed functionalities in various operational systems.

abstract: Motion estimation is a core task in computer vision and many applications utilize optical flow methods as fundamental tools to analyze motion in images and videos. Optical flow is the apparent motion of objects in image sequences that results from relative motion between the objects and the imaging perspective. Today, optical flow fields are utilized to solve problems in various areas such as object detection and tracking, interpolation, visual odometry, etc. In this dissertation, three problems from different areas of computer vision and the solutions that make use of modified optical flow methods are explained. The contributions of this dissertation are approaches and frameworks that introduce i) a new optical flow-based interpolation method to achieve minimally divergent velocimetry data, ii) a framework that improves the accuracy of change detection algorithms in synthetic aperture radar (SAR) images, and iii) a set of new methods to integrate Proton Magnetic Resonance Spectroscopy (1HMRSI) data into threedimensional (3D) neuronavigation systems for tumor biopsies. In the first application an optical flow-based approach for the interpolation of minimally divergent velocimetry data is proposed. The velocimetry data of incompressible fluids contain signals that describe the flow velocity. The approach uses the additional flow velocity information to guide the interpolation process towards reduced divergence in the interpolated data. In the second application a framework that mainly consists of optical flow methods and other image processing and computer vision techniques to improve object extraction from synthetic aperture radar images is proposed. The proposed framework is used for distinguishing between actual motion and detected motion due to misregistration in SAR image sets and it can lead to more accurate and meaningful change detection and improve object extraction from a SAR datasets. In the third application a set of new methods that aim to improve upon the current state-of-the-art in neuronavigation through the use of detailed three-dimensional (3D) 1H-MRSI data are proposed. The result is a progressive form of online MRSI-guided neuronavigation that is demonstrated through phantom validation and clinical application. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2018

A área de robótica móvel se encontra numa fase de grande expansão, mas um dos obstáculos a ser vencido é o desenvolvimento de sistemas computacionais embarcados que combinem baixo consumo de energia com alta capacidade de processamento. A computação reconfigurável tem o potencial para atender esta demanda. Este trabalho visa avaliar as dificuldades no aproveitamento desta tecnologia através da implementação em hardware de um sistema de desvio de obstáculos para robôs móveis usando uma única câmera de baixo custo como sensor. Normalmente os algorítmos de fluxo óptico usados neste projeto são implementados inteiramente em software e sofrem várias restrições para poderem operar nos computadores embarcados nos robôs. O projeto descrito neste trabalho não tem estas restrições mas exige um esforço maior de desenvolvimento / The area of mobile robotics is undergoing a tremendous expansion, but one of the obstacles to be dealt with is the development of embedded computational systems that combine low power consumption and high performance. Reconfigurable computing has the potential to meet these requirements. This project is an evaluation of the complexities of fully exploiting this technology through the hardware implementation of an obstacle avoidance system for mobile robots using a single, low cost camera as its sensor. Normally, the optic flow algorithms used in this project are implemented entirely in software and so suffer several limitations in order to run on computers embedded in the robots. The hardware described here does not have the same limitations but requires more development effort

<p>En modern grafikprocessor är oerhört kraftfull och har en prestanda som potentiellt sett är många gånger högre än för en modern mikroprocessor. I takt med att grafikprocessorn blivit alltmer programmerbar har det blivit möjligt att använda den för beräkningstunga tillämpningar utanför dess normala användningsområde. Inom det här arbetet utreds vilka möjligheter och begränsningar som uppstår vid användandet av grafikprocessorer för generell programmering. Arbetet inriktas främst mot signal- och bildbehandlingstillämpningar men mycket av principerna är tillämpliga även inom andra områden.</p><p>Ett ramverk för bildbehandling implementeras och några algoritmer inom bildanalys realiseras och utvärderas, bland annat stereoseende och beräkning av optiskt flöde. Resultaten visar på att vissa tillämpningar kan uppvisa en avsevärd prestandaökning i en grafikprocessor jämfört med i en mikroprocessor men att andra tillämpningar kan vara ineffektiva eller mycket svåra att implementera.</p> / <p>The modern graphical processing unit, GPU, is an extremely powerful unit, potentially many times more powerful than a modern microprocessor. Due to its increasing programmability it has recently become possible to use it in computation intensive applications outside its normal usage. This work investigates the possibilities and limitations of general purpose programming on GPUs. The work mainly concentrates on signal and image processing although much of the principles are applicable to other areas as well.</p><p>A framework for image processing on GPUs is implemented and a few computer vision algorithms are implemented and evaluated, among them stereo vision and optical flow. The results show that some applications can gain a substantial speedup when implemented correctly in the GPU but others can be inefficent or extremly hard to implement.</p>