Robust audiovisual speech recognition using noise-adaptive linear discriminant analysis

© 2016 IEEE.Automatic speech recognition (ASR) has become a widespread and convenient mode of human-machine interaction, but it is still not sufficiently reliable when used under highly noisy or reverberant conditions. One option for achieving far greater robustness is to include another modality that is unaffected by acoustic noise, such as video information. Currently the most successful approaches for such audiovisual ASR systems, coupled hidden Markov models (HMMs) and turbo decoding, both allow for slight asynchrony between audio and video features, and significantly improve recognition rates in this way. However, both typically still neglect residual errors in the estimation of audio features, so-called observation uncertainties. This paper compares two strategies for adding these observation uncertainties into the decoder, and shows that significant recognition rate improvements are achievable for both coupled HMMs and turbo decoding

Content-Aware Multimedia Communications

The demands for fast, economic and reliable dissemination of multimedia information are steadily growing within our society. While people and economy increasingly rely on communication technologies, engineers still struggle with their growing complexity. Complexity in multimedia communication originates from several sources. The most prominent is the unreliability of packet networks like the Internet. Recent advances in scheduling and error control mechanisms for streaming protocols have shown that the quality and robustness of multimedia delivery can be improved significantly when protocols are aware of the content they deliver. However, the proposed mechanisms require close cooperation between transport systems and application layers which increases the overall system complexity. Current approaches also require expensive metrics and focus on special encoding formats only. A general and efficient model is missing so far. This thesis presents efficient and format-independent solutions to support cross-layer coordination in system architectures. In particular, the first contribution of this work is a generic dependency model that enables transport layers to access content-specific properties of media streams, such as dependencies between data units and their importance. The second contribution is the design of a programming model for streaming communication and its implementation as a middleware architecture. The programming model hides the complexity of protocol stacks behind simple programming abstractions, but exposes cross-layer control and monitoring options to application programmers. For example, our interfaces allow programmers to choose appropriate failure semantics at design time while they can refine error protection and visibility of low-level errors at run-time. Based on some examples we show how our middleware simplifies the integration of stream-based communication into large-scale application architectures. An important result of this work is that despite cross-layer cooperation, neither application nor transport protocol designers experience an increase in complexity. Application programmers can even reuse existing streaming protocols which effectively increases system robustness.Der Bedarf unsere Gesellschaft nach kostengünstiger und zuverlässiger Kommunikation wächst stetig. Während wir uns selbst immer mehr von modernen Kommunikationstechnologien abhängig machen, müssen die Ingenieure dieser Technologien sowohl den Bedarf nach schneller Einführung neuer Produkte befriedigen als auch die wachsende Komplexität der Systeme beherrschen. Gerade die Übertragung multimedialer Inhalte wie Video und Audiodaten ist nicht trivial. Einer der prominentesten Gründe dafür ist die Unzuverlässigkeit heutiger Netzwerke, wie z.B.~dem Internet. Paketverluste und schwankende Laufzeiten können die Darstellungsqualität massiv beeinträchtigen. Wie jüngste Entwicklungen im Bereich der Streaming-Protokolle zeigen, sind jedoch Qualität und Robustheit der Übertragung effizient kontrollierbar, wenn Streamingprotokolle Informationen über den Inhalt der transportierten Daten ausnutzen. Existierende Ansätze, die den Inhalt von Multimediadatenströmen beschreiben, sind allerdings meist auf einzelne Kompressionsverfahren spezialisiert und verwenden berechnungsintensive Metriken. Das reduziert ihren praktischen Nutzen deutlich. Außerdem erfordert der Informationsaustausch eine enge Kooperation zwischen Applikationen und Transportschichten. Da allerdings die Schnittstellen aktueller Systemarchitekturen nicht darauf vorbereitet sind, müssen entweder die Schnittstellen erweitert oder alternative Architekturkonzepte geschaffen werden. Die Gefahr beider Varianten ist jedoch, dass sich die Komplexität eines Systems dadurch weiter erhöhen kann. Das zentrale Ziel dieser Dissertation ist es deshalb, schichtenübergreifende Koordination bei gleichzeitiger Reduzierung der Komplexität zu erreichen. Hier leistet die Arbeit zwei Beträge zum aktuellen Stand der Forschung. Erstens definiert sie ein universelles Modell zur Beschreibung von Inhaltsattributen, wie Wichtigkeiten und Abhängigkeitsbeziehungen innerhalb eines Datenstroms. Transportschichten können dieses Wissen zur effizienten Fehlerkontrolle verwenden. Zweitens beschreibt die Arbeit das Noja Programmiermodell für multimediale Middleware. Noja definiert Abstraktionen zur Übertragung und Kontrolle multimedialer Ströme, die die Koordination von Streamingprotokollen mit Applikationen ermöglichen. Zum Beispiel können Programmierer geeignete Fehlersemantiken und Kommunikationstopologien auswählen und den konkreten Fehlerschutz dann zur Laufzeit verfeinern und kontrolliere

Three-dimensional media for mobile devices

Cataloged from PDF version of article.This paper aims at providing an overview of the core technologies enabling the delivery of 3-D Media to next-generation mobile devices. To succeed in the design of the corresponding system, a profound knowledge about the human visual system and the visual cues that form the perception of depth, combined with understanding of the user requirements for designing user experience for mobile 3-D media, are required. These aspects are addressed first and related with the critical parts of the generic system within a novel user-centered research framework. Next-generation mobile devices are characterized through their portable 3-D displays, as those are considered critical for enabling a genuine 3-D experience on mobiles. Quality of 3-D content is emphasized as the most important factor for the adoption of the new technology. Quality is characterized through the most typical, 3-D-specific visual artifacts on portable 3-D displays and through subjective tests addressing the acceptance and satisfaction of different 3-D video representation, coding, and transmission methods. An emphasis is put on 3-D video broadcast over digital video broadcasting-handheld (DVB-H) in order to illustrate the importance of the joint source-channel optimization of 3-D video for its efficient compression and robust transmission over error-prone channels. The comparative results obtained identify the best coding and transmission approaches and enlighten the interaction between video quality and depth perception along with the influence of the context of media use. Finally, the paper speculates on the role and place of 3-D multimedia mobile devices in the future internet continuum involving the users in cocreation and refining of rich 3-D media content

VIDEO PREPROCESSING BASED ON HUMAN PERCEPTION FOR TELESURGERY

Video transmission plays a critical role in robotic telesurgery because of the high bandwidth and high quality requirement. The goal of this dissertation is to find a preprocessing method based on human visual perception for telesurgical video, so that when preprocessed image sequences are passed to the video encoder, the bandwidth can be reallocated from non-essential surrounding regions to the region of interest, ensuring excellent image quality of critical regions (e.g. surgical region). It can also be considered as a quality control scheme that will gracefully degrade the video quality in the presence of network congestion. The proposed preprocessing method can be separated into two major parts. First, we propose a time-varying attention map whose value is highest at the gazing point and falls off progressively towards the periphery. Second, we propose adaptive spatial filtering and the parameters of which are adjusted according to the attention map. By adding visual adaptation to the spatial filtering, telesurgical video data can be compressed efficiently because of the high degree of visual redundancy removal by our algorithm. Our experimental results have shown that with the proposed preprocessing method, over half of the bandwidth can be reduced while there is no significant visual effect for the observer. We have also developed an optimal parameter selecting algorithm, so that when the network bandwidth is limited, the overall visual distortion after preprocessing is minimized

Space Communications: Theory and Applications. Volume 3: Information Processing and Advanced Techniques. A Bibliography, 1958 - 1963

Annotated bibliography on information processing and advanced communication techniques - theory and applications of space communication

Energy efficient enabling technologies for semantic video processing on mobile devices

Semantic object-based processing will play an increasingly important role in future multimedia systems due to the ubiquity of digital multimedia capture/playback technologies and increasing storage capacity. Although the object based paradigm has many undeniable benefits, numerous technical challenges remain before the applications becomes pervasive, particularly on computational constrained mobile devices. A fundamental issue is the ill-posed problem of semantic object segmentation. Furthermore, on battery powered mobile computing devices, the additional algorithmic complexity of semantic object based processing compared to conventional video processing is highly undesirable both from a real-time operation and battery life perspective. This thesis attempts to tackle these issues by firstly constraining the solution space and focusing on the human face as a primary semantic concept of use to users of mobile devices. A novel face detection algorithm is proposed, which from the outset was designed to be amenable to be offloaded from the host microprocessor to dedicated hardware, thereby providing real-time performance and reducing power consumption. The algorithm uses an Artificial Neural Network (ANN), whose topology and weights are evolved via a genetic algorithm (GA). The computational burden of the ANN evaluation is offloaded to a dedicated hardware accelerator, which is capable of processing any evolved network topology. Efficient arithmetic circuitry, which leverages modified Booth recoding, column compressors and carry save adders, is adopted throughout the design. To tackle the increased computational costs associated with object tracking or object based shape encoding, a novel energy efficient binary motion estimation architecture is proposed. Energy is reduced in the proposed motion estimation architecture by minimising the redundant operations inherent in the binary data. Both architectures are shown to compare favourable with the relevant prior art

A motion-based approach for audio-visual automatic speech recognition

The research work presented in this thesis introduces novel approaches for both visual region of interest extraction and visual feature extraction for use in audio-visual automatic speech recognition. In particular, the speaker‘s movement that occurs during speech is used to isolate the mouth region in video sequences and motionbased features obtained from this region are used to provide new visual features for audio-visual automatic speech recognition. The mouth region extraction approach proposed in this work is shown to give superior performance compared with existing colour-based lip segmentation methods. The new features are obtained from three separate representations of motion in the region of interest, namely the difference in luminance between successive images, block matching based motion vectors and optical flow. The new visual features are found to improve visual-only and audiovisual speech recognition performance when compared with the commonly-used appearance feature-based methods. In addition, a novel approach is proposed for visual feature extraction from either the discrete cosine transform or discrete wavelet transform representations of the mouth region of the speaker. In this work, the image transform is explored from a new viewpoint of data discrimination; in contrast to the more conventional data preservation viewpoint. The main findings of this work are that audio-visual automatic speech recognition systems using the new features extracted from the frequency bands selected according to their discriminatory abilities generally outperform those using features designed for data preservation. To establish the noise robustness of the new features proposed in this work, their performance has been studied in presence of a range of different types of noise and at various signal-to-noise ratios. In these experiments, the audio-visual automatic speech recognition systems based on the new approaches were found to give superior performance both to audio-visual systems using appearance based features and to audio-only speech recognition systems