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Rozprawy doktorskie na temat "Codage vidéo sémantique"
Hammiche, Samira. "Approximation de requêtes dans les bases de données multimédia". Lyon 1, 2007. http://www.theses.fr/2007LYO10080.
Pełny tekst źródłaSamrouth, Khouloud. "Représentation et compression à haut niveau sémantique d’images 3D". Thesis, Rennes, INSA, 2014. http://www.theses.fr/2014ISAR0025/document.
Pełny tekst źródłaDissemination of multimedia data, in particular the images, continues to grow very significantly. Therefore, developing effective image coding schemes remains a very active research area. Today, one of the most innovative technologies in this area is the 3D technology. This 3D technology is widely used in many domains such as entertainment, medical imaging, education and very recently in criminal investigations. There are different ways of representing 3D information. One of the most common representations, is to associate a depth image to a classic colour image called texture. This joint representation allows a good 3D reconstruction, as the two images are well correlated, especially along the contours of the depth image. Therefore, in comparison with conventional 2D images, knowledge of the depth of field for 3D images provides an important semantic information about the composition of the scene. In this thesis, we propose a scalable 3D image coding scheme for 2D + depth representation with advanced functionalities, which preserves all the semantics present in the images, while maintaining a significant coding efficiency. The concept of preserving the semantics can be translated in terms of features such as an automatic extraction of regions of interest, the ability to encode the regions of interest with higher quality than the background, the post-production of the scene and the indexing. Thus, firstly we introduce a joint and scalable 2D plus depth coding scheme. First, texture is coded jointly with depth at low resolution, and a method of depth data compression well suited to the characteristics of the depth maps is proposed. This method exploits the strong correlation between the depth map and the texture to better encode the depth map. Then, a high resolution coding scheme is proposed in order to refine the texture quality. Next, we present a global fine representation and contentbased coding scheme. Therefore, we propose a representation and coding scheme based on "Depth of Interest", called "3D Autofocus". It consists in a fine extraction of objects, while preserving the contours in the depth map, and it allows to automatically focus on a particular depth zone, for a high rendering quality. Finally, we propose 3D image segmentation, providing a high consistency between colour, depth and regions of the scene. Based on a joint exploitation of the colour and depth information, this algorithm allows the segmentation of the scene with a level of granularity depending on the intended application. Based on such representation of the scene, it is possible to simply apply the same previous 3D Autofocus, for Depth of Interest extraction and coding. It is remarkable that both approaches ensure a high spatial coherence between texture, depth, and regions, allowing to minimize the distortions along object of interest's contours and then a higher quality in the synthesized views
Mitrica, Iulia. "Video compression of airplane cockpit screens content". Electronic Thesis or Diss., Institut polytechnique de Paris, 2021. http://www.theses.fr/2021IPPAT042.
Pełny tekst źródłaThis thesis addresses the problem of encoding the video of airplane cockpits.The cockpit of modern airliners consists in one or more screens displaying the status of the plane instruments (e.g., the plane location as reported by the GPS, the fuel level as read by the sensors in the tanks, etc.,) often superimposed over natural images (e.g., navigation maps, outdoor cameras, etc.).Plane sensors are usually inaccessible due to security reasons, so recording the cockpit is often the only way to log vital plane data in the event of, e.g., an accident.Constraints on the recording storage available on-board require the cockpit video to be coded at low to very low bitrates, whereas safety reasons require the textual information to remain intelligible after decoding. In addition, constraints on the power envelope of avionic devices limit the cockpit recording subsystem complexity.Over the years, a number of schemes for coding images or videos with mixed computer-generated and natural contents have been proposed. Text and other computer generated graphics yield high-frequency components in the transformed domain. Therefore, the loss due to compression may hinder the readability of the video and thus its usefulness. For example, the recently standardized Screen Content Coding (SCC) extension of the H.265/HEVC standard includes tools designed explicitly for screen contents compression. Our experiments show however that artifacts persist at the low bitrates targeted by our application, prompting for schemes where the video is not encoded in the pixel domain.This thesis proposes methods for low complexity screen coding where text and graphical primitives are encoded in terms of their semantics rather than as blocks of pixels.At the encoder side, characters are detected and read using a convolutional neural network.Detected characters are then removed from screen via pixel inpainting, yielding a smoother residual video with fewer high frequencies. The residual video is encoded with a standard video codec and is transmitted to the receiver side together with text and graphics semantics as side information.At the decoder side, text and graphics are synthesized using the decoded semantics and superimposed over the residual video, eventually recovering the original frame. Our experiments show that an AVC/H.264 encoder retrofitted with our method has better rate-distortion performance than H.265/HEVC and approaches that of its SCC extension.If the complexity constraints allow inter-frame prediction, we also exploit the fact that co-located characters in neighbor frames are strongly correlated.Namely, the misclassified symbols are recovered using a proposed method based on low-complexity model of transitional probabilities for characters and graphics. Concerning character recognition, the error rate drops up to 18 times in the easiest cases and at least 1.5 times in the most difficult sequences despite complex occlusions.By exploiting temporal redundancy, our scheme further improves in rate-distortion terms and enables quasi-errorless character decoding. Experiments with real cockpit video footage show large rate-distortion gains for the proposed method with respect to video compression standards
Kimiaei, Asadi Mariam. "Adaptation de contenu multimedia avec MPEG 21 : conversion de ressources et adaptation sémantique de scènes". Paris, ENST, 2005. http://www.theses.fr/2005ENST0040.
Pełny tekst źródłaThe objective of this Ph. D. Thesis is to propose new, simple and efficient techniques and methodologies for support of multimedia content adaptation to constrained contexts. The work is based on parts of the on-going MPEG-21 standard that aims at defining different components of a multimedia distribution framework. The thesis is divided into two main parts: single media adaptation and semantic adaptation of multimedia composed documents. In single media adaptation, the media is adapted to the context constraints, such as terminal capabilities, user preferences, network capacities, author recommendations and etc. In this type of adaptation, the media is considered solely, i. E. As mono media. We have defined description tools extending the MPEG-21 DIA schema, for description of hints and suggestions on different media adaptations and their corresponding parameters. In semantic adaptation of structured multimedia documents, we addressed the question of adaptation based on temporal, spatial and semantic relationships between the media objects. When adapting a multimedia presentation, in order to preserve the consistency and meaningfulness of the adapted scene, the adaptation process needs to have access to the semantic information of the presentation. We have defined a language as a set of descriptors, for the expression of semantic information of composed multimedia content. In our implementations, we used SMIL 2. 0 for describing multimedia scenes
Joveski, Bojan. "Dispositif de rendu distant multimédia et sémantique pour terminaux légers collaboratifs". Phd thesis, Ecole Nationale Supérieure des Mines de Paris, 2012. http://pastel.archives-ouvertes.fr/pastel-00873162.
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