A evolução das Tecnologias de Informação e Comunicação (TIC) favoreceu o crescimento do uso de variados meios na comunicação. Entre diversos meios, o vídeo em particular, necessita de uma grande banda para ser transmitido, ou de um grande espaço para ser armazenado. Uma análise dos diversos sinais de uma comunicação multimídia mostra, entretanto, que existe uma grande redundância de informação. Utilizando técnicas de compressão é possível reduzir de uma a duas ordens de grandeza a quantidade de informação veiculada, mantendo uma qualidade satisfatória. Uma das formas de compressão busca a relação de similaridade entre os quadros vizinhos de uma cena, identificando a redundância temporal existente entre as imagens. Essa técnica chama-se estimação de movimento, este processo é muito eficaz, mas o custo computacional é elevado, exigindo a implementação de algoritmos eficientes em hardware, para o caso de compressão em tempo real de vídeos de alta resolução. Esta dissertação apresenta uma investigação sobre algoritmos de estimação de movimento visando implementações em hardware. Todos os algoritmos foram desenvolvidos primeiramente em linguagem C e submetidos a diversos testes para avaliação de desempenho e custo computacional. Os algoritmos foram aplicados a diversas amostras de vídeo utilizadas pela comunidade científica, para avaliação em aplicações reais. As avaliações demonstraram que os algoritmos rápidos conseguem realizar o processo de estimação de movimento de maneira eficiente, obtendo bons resultados em termos de qualidade de vetores, esforço computacional e desempenho. Com as análises dos resultados obtidos, o algoritmo Busca Diamante (Diamond Search) foi escolhido para ser implementado em hardware, com dois níveis diferentes de subamostragem de pixel: 2:1 e 4:1. As arquiteturas para o algoritmo Busca Diamante, com sub-amostragem de pixel de 2:1 e 4:1, foram descritas em VHDL, sintetizadas para FPGAs Virtex-4 da Xilinx e também para standard cells na tecnologia TSMC 0,18μm. Os resultados mostram que as arquiteturas desenvolvidas possuem desempenho superior ao necessário para tratar vídeos HDTV 1080p em tempo real a 30 quadros por segundo. As arquiteturas desenvolvidas também apresentam um baixo consumo de recursos de hardware, após a síntese para FPGA e ASIC. / The evolution of the communication and information technologies push the development of several communication media. These media, video in particular, need a large bandwidth to be transmitted, or a large digital storage capacity. Many multimedia signals show, however, a high information redundancy. By using compression techniques it is possible to reduce the amount of coded information by one or two orders of magnitude, keeping a satisfactory visual quality. One of these compression techniques searches the similarity between neighboring frames of a scene, identifying the temporal redundancy between them. This technique is called motion estimation, and it is a very efficient method for compression. However, the computational complexity of the motion estimation requires high performance algorithms in hardware, when used for real time compression of high resolution videos. This dissertation presents a comprehensive investigation about motion estimation algorithms, targeting a hardware implementation. All the investigated algorithms were first developed in C language and submitted to many evaluation tests. The algorithms were applied to ten video samples used by the scientific community for the evaluation of real application. The evaluation showed that fast algorithms can carry out the motion estimation process efficiently, producing good results in vectors quality, computational effort and performance. With the results analyses, the Diamond Search algorithm was chosen to be hardware designed, with two different levels of pixel subsampling, 2:1 and 4:1. The architectures for Diamond Search algorithm, with pixel subsampling of 2:1 and 4:1, were described in VHDL, synthesized to Xilinx Virtex-4 FPGAs and also to standard cells TSMC 0.18μm technology. The developed architectures have sufficient performance to process HDTV 1080p videos at 30 frames per second and demand small hardware resources consumption after synthesis to FPGA and ASIC. Keywords: Video compression, motion estimation, VLSI design.

Les architectures mixtes contenant des composants programmables et d'autres reconfigurables peuvent fournir les performances de calcul nécessaires pour satisfaire les contraintes imposées aux applications temps réel. Mais l'implantation et d'optimisation de ces applications temps réel sur ce type d'architectures est une tâche complexe qui prend un temps énorme. Dans ce contexte, nous proposons un outil de prototypage rapide visant ce type d'architectures. Cet outil se base sur une extension que nous proposons de la méthodologie Adéquation Algorithme Architecture (AAA). Il permet d'effectuer automatiquement le partitionnement et l'ordonnancement optimisés des opérations de l'application sur les composants de l'architecture cible et la génération automatique des codes correspondants. Nous avons utilisé cet outil pour l'implantation de l'estimateur de mouvement de la norme H.264/AVC sur une architecture composée d'un processeur NIOS II d'Altera et d'un FPGA Stratix III. Ainsi nous avons pu vérifier le bon fonctionnement de notre outil et validé notre générateur automatique de code mixte / Mixed architectures containing programmable devices and reconfigurable ones can provide calculation performance necessary to meet constraints of real-time applications. But the implementation and optimization of these applications on this kind of architectures is a complex task that takes a lot of time. In this context, we propose a rapid prototyping tool for this type of architectures. This tool is based on our extension of the Adequacy Algorithm Architecture methodology (AAA). It allows to automatically perform optimized partitioning and scheduling of the application operations on the target architecture components and generation of correspondent codes. We used this tool for the implementation of the motion estimator of the H.264/AVC on an architecture composed of a Nios II processor and Altera Stratix III FPGA. So we were able to verify the correct running of our tool and validate our automatic generator of mixed code

This thesis presents the rate distortion analysis of conditional motion estimation, a process in which motion computation is restricted to only active pixels in the video. We model active pixels as independent and identically distributed Gaussian process and inactive pixels as Gaussian-Markov process and derive the rate distortion function based on conditional motion estimation. Rate-Distortion curves for the conditional motion estimation scheme are also presented. In addition this thesis also presents the hardware implementation of a block based motion estimation algorithm. Block matching algorithms are difficult to implement on FPGA chip due to its complexity. We implement 2D-Logarithmic search algorithm to estimate the motion vectors for the image. The matching criterion used in the algorithm is Sum of Absolute Differences (SAD). VHDL code for the motion estimation algorithm is verified using ISim and is implemented using Xilinx ISE Design tool. Synthesis results for the algorithm are also presented.

Recent reports suggest that measuring the objective quality is very essential towards the success of colonoscopy. Several quality indicators (i.e. metrics) proposed in recent studies are implemented in software systems that compute real-time quality scores for routine screening colonoscopy. Most quality metrics are derived based on various temporal events occurred during the colonoscopy procedure. The location of the phase boundary between the insertion and the withdrawal phases and the amount of circumferential inspection are two such important temporal events. These two temporal events can be determined by analyzing various camera motions of the colonoscope. This dissertation put forward a novel method to estimate X, Y and Z directional motions of the colonoscope using motion vector templates. Since abnormalities of a WCE or a colonoscopy video can be found in a small number of frames (around 5% out of total frames), it is very helpful if a computer system can decide whether a frame has any mucosal abnormalities. Also, the number of detected abnormal lesions during a procedure is used as a quality indicator. Majority of the existing abnormal detection methods focus on detecting only one type of abnormality or the overall accuracies are somewhat low if the method tries to detect multiple abnormalities. Most abnormalities in endoscopy images have unique textures which are clearly distinguishable from normal textures. In this dissertation a new method is proposed that achieves the objective of detecting multiple abnormalities with a higher accuracy using a multi-texture analysis technique. The multi-texture analysis method is designed by representing WCE and colonoscopy image textures as textons.

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Recently, video has become one of the most important multimedia resources to be shared in our work and daily life. With the development of high frame rate video (HFV), the write speed from high speed camera array sensor to the massive data storage device has been regarded as the main constraints on HFV applications. In this thesis, some low-complexity compression techniques are proposed for HFV acquisition and transmission. The core technique of our developed codec is the application of Slepian-Wolf coding theorem in video compression. The light-duty encoder employs SW encoding, resulting in lower computational cost. The pixel values are transformed into bit sequences, and then we assemble the bits on same bit plane into 8 bit streams. For each bit plane, there is a statistical BSC being constructed to describe the dependency between the source image and the SI image. Furthermore, an improved coding scheme is applied to exploit the spatial correlation between two consecutive bit planes, which is able to reduce the source coding rates. Different from the encoder, the collaborative heavy-duty decoder shoulders the burden of realizing high reconstruction fidelity. Motion estimation and motion compensation employ the block-matching algorithm to predict the SI image. And then the received syndrome sequence is able to be SW decoded with SI. To realize different compression goals, compression are separated to the original and the downsampled cases. With regard to the compression at the original resolution, it completes after SW decoding. While with respect to compression at reduced resolution, the SW decoded image is necessary to be upsampled by the state-of-the-art learning based SR technique: A+ . Since there are some important image details lost after the resolution resizing, ME and MC is applied to modify the upsampled image again, promoting the reconstruction PSNR. Experimental results show that the proposed low-complexity compression techniques are effective on improving reconstruction fidelity and compression ratio. / Thesis / Master of Applied Science (MASc)

Motion estimation and motion compensation comprise one of the most important compression methods for video communications. We propose a low-power design of a motion estimation block for a low bit-rate video codec standard H.263. Since the motion estimation is computationally intensive to result in large power consumption, a low-power design is essential for portable or mobile systems. Our block employs the Four-Step Search (4SS) method as its primary algorithm. The design and the algorithm have been optimized to provide adequate results for low-quality video at low-power consumption. The model is developed in VHDL and synthesized using a 0.35 um CMOS library. Power consumption of both gate-level circuits and memory-accesses have been considered. Gate-level simulation shows the proposed design offers a 38% power reduction over a "baseline" implementation of a 4SS model and a 60% power reduction over a baseline Three-Step Search (TSS) model. Power savings through reduction of memory access is 26% over the TSS model and 32% over the 4SS model. The total power consumption of the proposed motion estimation block ranges from 7 - 9 mW and is dependent on the type of video being motion estimated. / Master of Science

This paper describes a complete algorithm to estimate the motion of a fixed-wing aircraft given a series of digitized flight images. The algorithm was designed for fixed-wing aircraft because carefully procured flight images and corresponding navigation data were available to us for testing. After image pre-processing, optic flow data is determined by automatically finding and tracking good features between pairs of images. The image coordinates of matched features are then processed by a rigid-object linear optic flow-motion estimation algorithm. Input factors are weighed to provide good testing techniques. Error analysis is performed with simulation data keeping these factors in mind to determine the effectiveness of the optic flow algorithm. The output of this program is an estimate of rotation and translation of the imaged environment in relation to the camera, and thereby the airplane. Real flight images from NASA test flights are used to confirm the accuracy of the algorithm. Where possible, the estimated motion parameters are compared with recorded flight instrument data to confirm the correctness of the algorithm. Results show that the algorithm is accurate to within a degree provided that enough optic flow feature points are tracked. / Master of Science

Due to the large influx of computers in our daily lives, human-computer interaction has become crucially important. For a long time, focusing on what users need has been critical for designing interaction methods. However, new perspective tends to extend this attitude to encompass how human desires, interests, and ambitions can be met and supported. This implies that the way we interact with computers should be revisited. Centralizing human values rather than user needs is of the utmost importance for providing new interaction techniques. These values drive our decisions and actions, and are essential to what makes us human. This motivated us to introduce new interaction methods that will support human values, particularly human well-being. The aim of this thesis is to design new interaction methods that will empower human to have a healthy, intuitive, and pleasurable interaction with tomorrow’s digital world. In order to achieve this aim, this research is concerned with developing theories and techniques for exploring interaction methods beyond keyboard and mouse, utilizing human body. Therefore, this thesis addresses a very fundamental problem, human motion analysis. Technical contributions of this thesis introduce computer vision-based, marker-less systems to estimate and analyze body motion. The main focus of this research work is on head and hand motion analysis due to the fact that they are the most frequently used body parts for interacting with computers. This thesis gives an insight into the technical challenges and provides new perspectives and robust techniques for solving the problem.

Nowadays, there exist a huge number of end devices with different screen properties for watching television content, which is either broadcasted or transmitted over the internet. To allow best viewing conditions on each of these devices, different image formats have to be provided by the broadcaster. Producing content for every single format is, however, not applicable by the broadcaster as it is much too laborious and costly. The most obvious solution for providing multiple image formats is to produce one high resolution format and prepare formats of lower resolution from this. One possibility to do this is to simply scale video images to the resolution of the target image format. Two significant drawbacks are the loss of image details through ownscaling and possibly unused image areas due to letter- or pillarboxes. A preferable solution is to find the contextual most important region in the high-resolution format at first and crop this area with an aspect ratio of the target image format afterwards. On the other hand, defining the contextual most important region manually is very time consuming. Trying to apply that to live productions would be nearly impossible. Therefore, some approaches exist that automatically define cropping areas. To do so, they extract visual features, like moving reas in a video, and define regions of interest (ROIs) based on those. ROIs are finally used to define an enclosing cropping area. The extraction of features is done without any knowledge about the type of content. Hence, these approaches are not able to distinguish between features that might be important in a given context and those that are not. The work presented within this thesis tackles the problem of extracting visual features based on prior knowledge about the content. Such knowledge is fed into the system in form of metadata that is available from TV production environments. Based on the extracted features, ROIs are then defined and filtered dependent on the analysed content. As proof-of-concept, this application finally adapts SDTV (Standard Definition Television) sports productions automatically to image formats with lower resolution through intelligent cropping and scaling. If no content information is available, the system can still be applied on any type of content through a default mode. The presented approach is based on the principle of a plug-in system. Each plug-in represents a method for analysing video content information, either on a low level by extracting image features or on a higher level by processing extracted ROIs. The combination of plug-ins is determined by the incoming descriptive production metadata and hence can be adapted to each type of sport individually. The application has been comprehensively evaluated by comparing the results of the system against alternative cropping methods. This evaluation utilised videos which were manually cropped by a professional video editor, statically cropped videos and simply scaled, non-cropped videos. In addition to and apart from purely subjective evaluations, the gaze positions of subjects watching sports videos have been measured and compared to the regions of interest positions extracted by the system.