Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Ciência da Computação, 2013. / Submitted by Alaíde Gonçalves dos Santos (alaide@unb.br) on 2014-01-21T10:04:59Z No. of bitstreams: 1 2013_RenatoCoralSampaio.pdf: 3776105 bytes, checksum: ec34db0ab9261723cadcfe2fd5f9432e (MD5) / Approved for entry into archive by Guimaraes Jacqueline(jacqueline.guimaraes@bce.unb.br) on 2014-02-14T11:52:25Z (GMT) No. of bitstreams: 1 2013_RenatoCoralSampaio.pdf: 3776105 bytes, checksum: ec34db0ab9261723cadcfe2fd5f9432e (MD5) / Made available in DSpace on 2014-02-14T11:52:25Z (GMT). No. of bitstreams: 1 2013_RenatoCoralSampaio.pdf: 3776105 bytes, checksum: ec34db0ab9261723cadcfe2fd5f9432e (MD5) / A Codificação de áudio está presente hoje nos mais diversos aparelhos eletrônicos desde o rádio, a televisão, o computador, os tocadores de música portáteis e nos celulares. Em 2007, o governo do Brasil definiu o padrão do Sistema Brasileiro de TV Digital (SBTVD) que adotou o AAC Advanced Audio Coding para codificação de áudio. Neste trabalho, utilizamos a abordagem de coprojeto combinando software e hardware para implementar uma solução de alto desempenho e baixo consumo de energia em um FPGA, capaz de decodificar até 6 canais de áudio em tempo real. Apresentamos os detalhes da solução bem como os testes de desempenho e qualidade. Por fim, apresentamos os resultados de utilização de hardware e performance juntamente com uma comparação com as demais soluções encontradas na literatura. _______________________________________________________________________________________ ABSTRACT / Audio Coding is present today in many electronic devices. It can be found in radio, tv, computers, portable audio players and mobile phones. In 2007 the Brazilian Government defined the brazilian Digital TV System standard (SBTVD) and adopted the AAC - Advanced Audio Coding as the audio codec. In this work we use the co-design of hardware and software approach to implement a high performance and low energy solution on an FPGA, able to decode up to 6 channels of audio in real-time. The solution architecture and details are presented along with performance and quality tests. Finally, hardware usage and performance results are presented and compared to other solutions found in literature.

Audio coding is used to compress digital audio signals, thereby reducing the amount of bits needed to transmit or to store an audio signal. This is useful when network bandwidth or storage capacity is very limited. Audio compression algorithms are based on an encoding and decoding process. In the encoding step, the uncompressed audio signal is transformed into a coded representation, thereby compressing the audio signal. Thereafter, the coded audio signal eventually needs to be restored (e.g. for playing back) through decoding of the coded audio signal. The decoder receives the bitstream and reconverts it into an uncompressed signal. ISO-MPEG is a standard for high-quality, low bit-rate video and audio coding. The audio part of the standard is composed by algorithms for high-quality low-bit-rate audio coding, i.e. algorithms that reduce the original bit-rate, while guaranteeing high quality of the audio signal. The audio coding algorithms consists of MPEG-1 (with three different layers), MPEG-2, MPEG-2 AAC, and MPEG-4. This work presents a study of the MPEG-4 AAC audio coding algorithm. Besides, it presents the implementation of the AAC algorithm on different platforms, and comparisons among implementations. The implementations are in C language, in Assembly of Intel Pentium, in C-language using DSP processor, and in HDL. Since each implementation has its own application niche, each one is valid as a final solution. Moreover, another purpose of this work is the comparison among these implementations, considering estimated costs, execution time, and advantages and disadvantages of each one.

This thesis aims at building a system capable of automatically extracting and parameterizing the position of a face and its features in images acquired from a low-end monocular camera. Such a challenging task is justified by the importance and variety of its possible applications, ranging from face and expression recognition to animation of virtual characters using video depicting real actors. The implementation includes the construction of Active Appearance Models of the human face from training images. The existing face model Candide-3 is used as a starting point, making the translation of the tracking parameters to standard MPEG-4 Facial Animation Parameters easy. The Inverse Compositional Algorithm is employed to adapt the models to new images, working on a subspace where the appearance is "projected out" and thus focusing only on shape. The algorithm is tested on a generic model, aiming at tracking different people’s faces, and on a specific model, considering one person only. In the former case, the need for improvements in the robustness of the system is highlighted. By contrast, the latter case gives good results regarding both quality and speed, with real time performance being a feasible goal for future developments.

>Magister Scientiae - MSc / This thesis investigates the modelling and animation of virtual humans for real-time sign language visualisation. Sign languages are fully developed natural languages used by Deaf communities all over the world. These languages are communicated in a visual-gestural modality by the use of manual and non-manual gestures and are completely di erent from spoken languages. Manual gestures include the use of hand shapes, hand movements, hand locations and orientations of the palm in space. Non-manual gestures include the use of facial expressions, eye-gazes, head and upper body movements. Both manual and nonmanual gestures must be performed for sign languages to be correctly understood and interpreted. To e ectively visualise sign languages, a virtual human system must have models of adequate quality and be able to perform both manual and non-manual gesture animations in real-time. Our goal was to develop a methodology and establish an open framework by using various standards and open technologies to model and animate virtual humans of adequate quality to e ectively visualise sign languages. This open framework is to be used in a Machine Translation system that translates from a verbal language such as English to any sign language. Standards and technologies we employed include H-Anim, MakeHuman, Blender, Python and SignWriting. We found it necessary to adapt and extend H-Anim to e ectively visualise sign languages. The adaptations and extensions we made to H-Anim include imposing joint rotational limits, developing exible hands and the addition of facial bones based on the MPEG-4 Facial De nition Parameters facial feature points for facial animation. By using these standards and technologies, we found that we could circumvent a few di cult problems, such as: modelling high quality virtual humans; adapting and extending H-Anim; creating a sign language animation action vocabulary; blending between animations in an action vocabulary; sharing animation action data between our virtual humans; and e ectively visualising South African Sign Language. / South Africa

<p>H.264, also known as MPEG-4 Part 10: Advanced Video Coding, is the latest MPEG standard for video coding. It provides approximately 50% bit rate savings for equivalent perceptual quality compared to any previous standard. In the same fashion as previous MPEG standards, only the bitstream syntax and the decoder are specified. Hence, coding performance is not only determined by the standard itself but also by the implementation of the encoder. In this report we propose two methods for improving the coding performance while remaining fully compliant to the standard. </p><p>After transformation and quantization, the transform coefficients are usually entropy coded and embedded in the bitstream. However, some of them might be beneficial to discard if the number of saved bits are sufficiently large. This is usually referred to as coefficient thresholding and is investigated in the scope of H.264 in this report. </p><p>Lagrangian optimization for video compression has proven to yield substantial improvements in perceived quality and the H.264 Reference Software has been designed around this concept. When performing Lagrangian optimization, lambda is a crucial parameter that determines the tradeoff between rate and distortion. We propose a new method to select lambda and the quantization parameter for non-reference frames in H.264. </p><p>The two methods are shown to achieve significant improvements. When combined, they reduce the bitrate around 12%, while preserving the video quality in terms of average PSNR. </p><p>To aid development of H.264, a software tool has been created to visualize the coding process and present statistics. This tool is capable of displaying information such as bit distribution, motion vectors, predicted pictures and motion compensated block sizes.</p>

<p>ITU - T and the Moving Picture Expert Group (MPEG) have jointly, under the name of Joint Video Team (JVT), developed a new video coding standard. The standard is called H.264 and is also known as Advanced Video Coding (AVC) or MPEG-4 part 10. Comparisons shows that H.264 greatly outperforms MPEG-2, currently used in DVD and digital TV. H.264 halves the bit rate with equal image quality. The great rate - distortion performance means nevertheless a high computational complexity. Especially on the encoder side.</p><p>Handling of audio and video, e.g. compressing and filtering, is quite complex and requires high performance hardware and software. A video encoder consists of a number of modules that find the best coding parameters. For each macroblock several $modes$ are evaluated in order to achieve optimal coding. The reference implementation of H.264 uses a brute force search for this mode selection which is extremely computational constraining. In order to perform video encoding with satisfactory speed there is an obvious need for reducing the amount of modes that are evaluated.</p><p>This thesis proposes an algorithm which reduces the number of modes and reference frames that are evaluated. The algorithm can be regulated in order to fulfill the demand on quality versus speed. Six times faster encoding can be obtained without loosing perceptual image quality. By allowing some quality degradation the encoding becomes up to 20 times faster.</p>

<p>3D television using multiple views rendering is receiving increasing interest. In this technology a number of video sequences are transmitted simultaneously and provides a larger view of the scene or stereoscopic viewing experience. With two views stereoscopic rendition is possible. Nowadays 3D displays are available that are capable of displaying several views simultaneously and the user is able to see different views by moving his head.</p><p>The thesis work aims at implementing a demonstration system with a number of simultaneous views. The system will include two cameras, computers at both the transmitting and receiving end and a multi-view display. Besides setting up the hardware, the main task is to implement software so that the transmission can be done over an IP-network.</p><p>This thesis report includes an overview and experiences of similar published systems, the implementation of real time video, its compression, encoding, and transmission over the internet with the help of socket programming and finally the multi-view display in 3D format.  This report also describes the design considerations more precisely regarding the video coding and network protocols.</p>

<p>In this thesis we present a system to extract the eye motion from a video stream containing a human face and applying this eye motion into a virtual character. By the notation eye motion estimation, we mean the information which describes the location of the eyes in each frame of the video stream. Applying this eye motion estimation into a virtual character, we achieve that the virtual face moves the eyes in the same way than the human face, synthesizing eye motion into a virtual character. In this study, a system capable of face tracking, eye detection and extraction, and finally iris position extraction using video stream containing a human face has been developed. Once an image containing a human face is extracted from the current frame of the video stream, the detection and extraction of the eyes is applied. The detection and extraction of the eyes is based on edge detection. Then the iris center is determined applying different image preprocessing and region segmentation using edge features on the eye picture extracted.</p><p>Once, we have extracted the eye motion, using MPEG-4 Facial Animation, this motion is translated into the Facial Animation arameters (FAPs). Thus we can improve the quality and quantity of Facial Animation expressions that we can synthesize into a virtual character.</p>

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The use of computer animated interactive faces in film, TV, games is ever growing, with new application areas emerging also on the Internet and mobile environments. Morph targets are one of the most popular methods to animate the face. Up until now 3D artists had to design each morph target defined by the MPEG-4 standard by hand. This is a very monotonous and tedious task. With the newly developed method of Facial Motion Cloning [11]the heavy work is relieved from the artists. From an already animated face model the morph targets can now be copied onto a new static face model. For the Facial Motion Cloning process there must be a subset of the feature points specified by the MPEG-4 standard defined. The purpose of this is to correlate the facial features of the two faces. The goal of this project is to develop a graphical editor in which the artists can define the feature points for a face model. The feature points will be saved in a file format that can be used in a Facial Motion Cloning software.