774 resultados para Scalable video coding


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The production by biosynthesis of optically active amino acids and amines satisfies the pharmaceutical industry in its demand for chiral building blocks for the synthesis of various pharmaceuticals. Among several enzymatic methods that allow the synthesis of optically active aminoacids and amines, the use of minotransferase is a promising one due to its broad substrate specificity and no requirement for external cofactor regeneration. The synthesis of chiral compounds by aminotransferases can be done either by asymmetric synthesis starting from keto acids or ketones, and by kinetic resolution starting from racemic aminoacids or amines. The asymmetric synthesis of substituted (S)-aminotetralin, an active pharmaceutical ingredient (API), has shown to have two major factors that contribute to increasing the cost of production. These factors are the raw material cost of biocatalyst used to produce it and product loss during biocatalyst separation. To minimize the cost contribution of biocatalyst and to minimize the loss of product, two routes have been chosen in this research: 1. To engineer the aminotransferase biocatalyst to have greater specific activity, and 2. Improve the engineering of the process by immobilization of biocatalyst in calcium alginate and addition of cosolvents. An (S)-aminotransferase (Mutant CNB03-03) was immobilized, not as purified enzyme but as enzyme within spray dried cells, in calcium alginate beads and used to produce substituted (S)-aminotetralin at 50 °C and pH 7 in experiments where the immobilized biocatalyst was recycled. Initial rate of reaction for cycle 1 (6 hr duration) was determined to be 0.258 mM/min, for cycle 2 (20 hr duration) it decreased by ~50% compared to cycle 1, and for cycle 3 (20 hr duration) it decreased by ~90% compared to cycle 1 (immobilized preparation consisted of 50 mg of spray dried cells per gram of calcium alginate). Conversion to product for each cycle decreased as well, from 100% in cycle 1 (About 50 mM), 80% in cycle 2, and 30% after cycle 3. This mutant was determined to be deactivated at elevated temperatures during the reaction cycle and was not stable enough to allow multiple cycles in its immobilized form. A new mutant aminotransferase was isolated by applying error-prone polymerase chain reaction (PCR) on the gene coding for this enzyme and screening/selection: CNB04-01. This mutant showed a significant improvement in thermostability in comparison to CNB03-03. The new mutant was immobilized and tested under similar reaction conditions. Initial rate remained fairly constant (0.2 mM/min) over four cycles (each cycle with a duration of about 20 hours) with the mutant retaining almost 80% of initial rate in the fourth cycle. The final product concentrations after each cycle did not decrease during recycle experiments. Thermostability of CNB04-01 was much improved compared to CNB03-03. Under the same reaction conditions as stated above, the addition of co-solvents was studied in order to increase substituted tetralone solubility. Toluene and sodium dodecylsulfate (SDS) were used. SDS at 0.01% (w/v) allowed four recycles of the immobilized spray dried cells of CNB04-01, always reaching higher product concentration (80-85 mM) than the system with toluene at 3% (v/v) -70 mM-. The long term activity of immobilized CNB04-01 in a system with SDS 0.01% (w/v) at 50 °C, pH 7 was retained for three cycles (20 to 24 hours each one), reaching always final product concentration between 80-85 mM, but dropping precipitously in the fourth cycle to a final product concentration of 50 mM. Although significant improvement of immobilization on productivity and stability were observed using CNB04-01, another observation demonstrated the limitations of an immobilization strategy on reducing process costs. After analyzing the results of this experiment it was seen that a sudden drop occurred on final product concentration after the third recycle. This was due to product accumulation inside the immobilized preparation. In order to improve the economics of the process, research was focused on developing a free enzyme with an even higher activity, thus reducing raw material cost as well as improving biomass separation. A new enzyme was obtained (CNB05-01) using error-prone PCR and screening using as a template the gene derived from the previous improved enzyme. This mutant was determined to have 1.6 times the initial rate of CNB04-01 and had a higher temperature optimum (55°). This new enzyme would allow reducing enzyme loading in the reaction by five-fold compared to CNB03-03, when using it at concentration of one gram of spray dried cells per liter (completing the reaction after 20-24 hours). Also this mutant would allow reducing process time to 7-8 hours when used at a concentration of 5 grams of spray dried cells per liter compared to 24 hours for CNB03-03, assuming that the observations shown before are scalable. It could be possible to improve the economics of the process by either reducing enzyme concentration or reducing process time, since the production cost of the desired product is primarily a function of both enzyme concentration and process time.

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The explosion of multimedia digital content and the development of technologies that go beyond traditional broadcast and TV have rendered access to such content important for all end-users of these technologies. While originally developed for providing access to multimedia digital libraries, video search technologies assume now a more demanding role. In this paper, we attempt to shed light onto this new role of video search technologies, looking at the rapid developments in the related market, the lessons learned from state of art video search prototypes developed mainly in the digital libraries context and the new technological challenges that have risen. We focus on one of the latter, i.e., the development of cross-media decision mechanisms, drawing examples from REVEAL THIS, an FP6 project on the retrieval of video and language for the home user. We argue, that efficient video search holds a key to the usability of the new ”pervasive digital video” technologies and that it should involve cross-media decision mechanisms.

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Innovations in hardware and network technologies lead to an exploding number of non-interrelated parallel media streams. Per se this does not mean any additional value for consumers. Broadcasting and advertisement industries have not yet found new formats to reach the individual user with their content. In this work we propose and describe a novel digital broadcasting framework, which allows for the live staging of (mass) media events and improved consumer personalisation. In addition new professions for future TV production workflows which will emerge are described, namely the 'video composer' and the 'live video conductor'.

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This paper proposes a new compression algorithm for dynamic 3d meshes. In such a sequence of meshes, neighboring vertices have a strong tendency to behave similarly and the degree of dependencies between their locations in two successive frames is very large which can be efficiently exploited using a combination of Predictive and DCT coders (PDCT). Our strategy gathers mesh vertices of similar motions into clusters, establish a local coordinate frame (LCF) for each cluster and encodes frame by frame and each cluster separately. The vertices of each cluster have small variation over a time relative to the LCF. Therefore, the location of each new vertex is well predicted from its location in the previous frame relative to the LCF of its cluster. The difference between the original and the predicted local coordinates are then transformed into frequency domain using DCT. The resulting DCT coefficients are quantized and compressed with entropy coding. The original sequence of meshes can be reconstructed from only a few non-zero DCT coefficients without significant loss in visual quality. Experimental results show that our strategy outperforms or comes close to other coders.

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This paper presents an empirical study of affine invariant feature detectors to perform matching on video sequences of people with non-rigid surface deformation. Recent advances in feature detection and wide baseline matching have focused on static scenes. Video frames of human movement capture highly non-rigid deformation such as loose hair, cloth creases, skin stretching and free flowing clothing. This study evaluates the performance of six widely used feature detectors for sparse temporal correspondence on single view and multiple view video sequences. Quantitative evaluation is performed of both the number of features detected and their temporal matching against and without ground truth correspondence. Recall-accuracy analysis of feature matching is reported for temporal correspondence on single view and multiple view sequences of people with variation in clothing and movement. This analysis identifies that existing feature detection and matching algorithms are unreliable for fast movement with common clothing.

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In this paper we present a hybrid method to track human motions in real-time. With simplified marker sets and monocular video input, the strength of both marker-based and marker-free motion capturing are utilized: A cumbersome marker calibration is avoided while the robustness of the marker-free tracking is enhanced by referencing the tracked marker positions. An improved inverse kinematics solver is employed for real-time pose estimation. A computer-visionbased approach is applied to refine the pose estimation and reduce the ambiguity of the inverse kinematics solutions. We use this hybrid method to capture typical table tennis upper body movements in a real-time virtual reality application.

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Visual fixation is employed by humans and some animals to keep a specific 3D location at the center of the visual gaze. Inspired by this phenomenon in nature, this paper explores the idea to transfer this mechanism to the context of video stabilization for a handheld video camera. A novel approach is presented that stabilizes a video by fixating on automatically extracted 3D target points. This approach is different from existing automatic solutions that stabilize the video by smoothing. To determine the 3D target points, the recorded scene is analyzed with a stateof- the-art structure-from-motion algorithm, which estimates camera motion and reconstructs a 3D point cloud of the static scene objects. Special algorithms are presented that search either virtual or real 3D target points, which back-project close to the center of the image for as long a period of time as possible. The stabilization algorithm then transforms the original images of the sequence so that these 3D target points are kept exactly in the center of the image, which, in case of real 3D target points, produces a perfectly stable result at the image center. Furthermore, different methods of additional user interaction are investigated. It is shown that the stabilization process can easily be controlled and that it can be combined with state-of-theart tracking techniques in order to obtain a powerful image stabilization tool. The approach is evaluated on a variety of videos taken with a hand-held camera in natural scenes.

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This contribution discusses the effects of camera aperture correction in broadcast video on colour-based keying. The aperture correction is used to ’sharpen’ an image and is one element that distinguishes the ’TV-look’ from ’film-look’. ’If a very high level of sharpening is applied, as is the case in many TV productions then this significantly shifts the colours around object boundaries with hight contrast. This paper discusses these effects and their impact on keying and describes a simple low-pass filter to compensate for them. Tests with colour-based segmentation algorithms show that the proposed compensation is an effective way of decreasing the keying artefacts on object boundaries.

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We present an algorithm for estimating dense image correspondences. Our versatile approach lends itself to various tasks typical for video post-processing, including image morphing, optical flow estimation, stereo rectification, disparity/depth reconstruction, and baseline adjustment. We incorporate recent advances in feature matching, energy minimization, stereo vision, and data clustering into our approach. At the core of our correspondence estimation we use Efficient Belief Propagation for energy minimization. While state-of-the-art algorithms only work on thumbnail-sized images, our novel feature downsampling scheme in combination with a simple, yet efficient data term compression, can cope with high-resolution data. The incorporation of SIFT (Scale-Invariant Feature Transform) features into data term computation further resolves matching ambiguities, making long-range correspondence estimation possible. We detect occluded areas by evaluating the correspondence symmetry, we further apply Geodesic matting to automatically determine plausible values in these regions.