Готові списки джерел за темами / Spatial scalability

Добірка наукової літератури з теми "Spatial scalability"

Автор: Grafiati

Опубліковано: 10 грудня 2022

Оновлено: 28 січня 2023

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Статті в журналах з теми "Spatial scalability"

Li, Zhengguo G., Susanto Rahardja, and Huifang Sun. "Implicit Bit Allocation for Combined Coarse Granular Scalability and Spatial Scalability." IEEE Transactions on Circuits and Systems for Video Technology 16, no. 12 (December 2006): 1449–59. http://dx.doi.org/10.1109/tcsvt.2006.885176.

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Qingwen Hu and S. Panchanathan. "Image/video spatial scalability in compressed domain." IEEE Transactions on Industrial Electronics 45, no. 1 (1998): 23–31. http://dx.doi.org/10.1109/41.661301.

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Hu, Qingwen, and Sethuraman Pachanathan. "Image/video spatial scalability in compressed domain." Computer Standards & Interfaces 20, no. 6-7 (March 1999): 403–4. http://dx.doi.org/10.1016/s0920-5489(99)90757-2.

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Dugad, R., and N. Ahuja. "A scheme for spatial scalability using nonscalable encoders." IEEE Transactions on Circuits and Systems for Video Technology 13, no. 10 (October 2003): 993–99. http://dx.doi.org/10.1109/tcsvt.2003.816519.

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Thang, Truong Cong, Jung Won Kang, Jeong-Ju Yoo, and Yong Man Ro. "Optimal Multilayer Adaptation of SVC Video over Heterogeneous Environments." Advances in Multimedia 2008 (2008): 1–8. http://dx.doi.org/10.1155/2008/739192.

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Scalable video coding (SVC) is a new video coding format which provides scalability in three-dimensional (spatio-temporal-SNR) space. In this paper, we focus on the adaptation in SNR dimension. Usually, an SVC bitstream may contain multiple spatial layers, and each spatial layer may be enhanced by several FGS layers. To meet a bitrate constraint, the fine-grained scalability (FGS) data of different spatial layers can be truncated in various manners. However, the contributions of FGS layers to the overall/collective video quality are different. In this work, we propose an optimized framework to control the SNR scalability across multiple spatial layers. Our proposed framework has the flexibility in allocating the resource (i.e., bitrate) among spatial layers, where the overall quality is defined as a function of all spatial layers' qualities and can be modified on the fly.

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Kamath, Uday, Carlotta Domeniconi, and Kenneth De Jong. "Theoretical and Empirical Analysis of a Spatial EA Parallel Boosting Algorithm." Evolutionary Computation 26, no. 1 (March 2018): 43–66. http://dx.doi.org/10.1162/evco_a_00202.

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Many real-world problems involve massive amounts of data. Under these circumstances learning algorithms often become prohibitively expensive, making scalability a pressing issue to be addressed. A common approach is to perform sampling to reduce the size of the dataset and enable efficient learning. Alternatively, one customizes learning algorithms to achieve scalability. In either case, the key challenge is to obtain algorithmic efficiency without compromising the quality of the results. In this article we discuss a meta-learning algorithm (PSBML) that combines concepts from spatially structured evolutionary algorithms (SSEAs) with concepts from ensemble and boosting methodologies to achieve the desired scalability property. We present both theoretical and empirical analyses which show that PSBML preserves a critical property of boosting, specifically, convergence to a distribution centered around the margin. We then present additional empirical analyses showing that this meta-level algorithm provides a general and effective framework that can be used in combination with a variety of learning classifiers. We perform extensive experiments to investigate the trade-off achieved between scalability and accuracy, and robustness to noise, on both synthetic and real-world data. These empirical results corroborate our theoretical analysis, and demonstrate the potential of PSBML in achieving scalability without sacrificing accuracy.

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Wang, Z., and L. J. Lu. "Study on video signal processing for layered spatial scalability." Imaging Science Journal 60, no. 5 (October 2012): 243–47. http://dx.doi.org/10.1179/174313112x13197110618234.

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Naghdinezhad, Amir, and Fabrice Labeau. "Reference frame modification techniques for temporal and spatial scalability." Signal Processing: Image Communication 27, no. 10 (November 2012): 1079–95. http://dx.doi.org/10.1016/j.image.2012.09.001.

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Van der Auwera, Geert, Prasanth T. David, Martin Reisslein, and Lina J. Karam. "Traffic and Quality Characterization of the H.264/AVC Scalable Video Coding Extension." Advances in Multimedia 2008 (2008): 1–27. http://dx.doi.org/10.1155/2008/164027.

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The recent scalable video coding (SVC) extension to the H.264/AVC video coding standard has unprecedented compression efficiency while supporting a wide range of scalability modes, including temporal, spatial, and quality (SNR) scalability, as well as combined spatiotemporal SNR scalability. The traffic characteristics, especially the bit rate variabilities, of the individual layer streams critically affect their network transport. We study the SVC traffic statistics, including the bit rate distortion and bit rate variability distortion, with long CIF resolution video sequences and compare them with the corresponding MPEG-4 Part 2 traffic statistics. We consider (i) temporal scalability with three temporal layers, (ii) spatial scalability with a QCIF base layer and a CIF enhancement layer, as well as (iii) quality scalability modes FGS and MGS. We find that the significant improvement in RD efficiency of SVC is accompanied by substantially higher traffic variabilities as compared to the equivalent MPEG-4 Part 2 streams. We find that separately analyzing the traffic of temporal-scalability only encodings gives reasonable estimates of the traffic statistics of the temporal layers embedded in combined spatiotemporal encodings and in the base layer of combined FGS-temporal encodings. Overall, we find that SVC achieves significantly higher compression ratios than MPEG-4 Part 2, but produces unprecedented levels of traffic variability, thus presenting new challenges for the network transport of scalable video.

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Bayat, Mozhgan, Ratheesh K. Mungara, and Giuseppe Caire. "Achieving Spatial Scalability for Coded Caching via Coded Multipoint Multicasting." IEEE Transactions on Wireless Communications 18, no. 1 (January 2019): 227–40. http://dx.doi.org/10.1109/twc.2018.2878845.

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Дисертації з теми "Spatial scalability"

Cary, Ariel. "Scaling Geospatial Searches in Large Spatial Databases." FIU Digital Commons, 2011. http://digitalcommons.fiu.edu/etd/548.

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Modern geographical databases store a rich set of aspatial attributes in addition to geographic data. Retrieving spatial records constrained on spatial and aspatial attributes provides users the ability to perform more interesting spatial analyses via composite spatial searches; e.g., in a real estate database, "Find the nearest homes for sale to my current location that have backyard and whose prices are between $50,000 and $80,000". Efficient processing of such composite searches requires combined indexing strategies of multiple types of data. Existing spatial query engines commonly apply a two-filter approach (spatial filter followed by non-spatial filter, or viceversa), which can incur large performance overheads. On the other hand, the amount of geolocation data in databases is rapidly increasing due in part to advances in geolocation technologies (e.g., GPS- enabled mobile devices) that allow to associate location data to nearly every object or event. Hence, practical spatial databases may face data ingestion challenges of large data volumes. In this dissertation, we first show how indexing spatial data with R-trees (a typical data pre- processing task) can be scaled in MapReduce – a well-adopted parallel programming model, developed by Google, for data intensive problems. Close to linear scalability was observed in index construction tasks over large spatial datasets. Subsequently, we develop novel techniques for simultaneously indexing spatial with textual and numeric data to process k-nearest neighbor searches with aspatial Boolean selection constraints. In particular, numeric ranges are compactly encoded and explicitly indexed. Experimental evaluations with real spatial databases showed query response times within acceptable ranges for interactive search systems.

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Mollevik, Johan. "Natural language interfaces over spatial data : investigations in scalability, extensibility and reliability." Licentiate thesis, Umeå universitet, Institutionen för datavetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-87705.

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Thorne, Chris. "Origin-centric techniques for optimising scalability and the fidelity of motion, interaction and rendering." University of Western Australia. School of Computer Science and Software Engineering, 2008. http://theses.library.uwa.edu.au/adt-WU2008.0177.

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[Truncated abstract] This research addresses endemic problems in the fields of computer graphics and simulation such as jittery motion, spatial scalability, rendering problems such as z-buffer tearing, the repeatability of physics dynamics and numerical error in positional systems. Designers of simulation and computer graphics software tend to map real world navigation rules onto the virtual world, expecting to see equivalent virtual behaviour. After all, if computers are programmed to simulate the real world, it is reasonable to expect the virtual behaviour to correspond. However, in computer simulation many behaviours and other computations show measurable problems inconsistent with realworld experience, particularly at large distances from the virtual world origin. Many of these problems, particularly in rendering, can be imperceptible, so users may be oblivious to them, but they are measurable using experimental methods. These effects, generically termed spatial jitter in this thesis, are found in this study to stem from floating point error in positional parameters such as spatial coordinates. This simulation error increases with distance from the coordinate origin and as the simulation progresses through the pipeline. The most common form of simulation error relevant to this study is spatial error which is found by this thesis to not be calculated, as may be expected, using numerical relative error propagation rules but using the rules of geometry. ... The thesis shows that the thinking behind real-world rules, such as for navigation, has to change in order to properly design for optimal fidelity simulation. Origincentric techniques, formulae, terms, architecture and processes are all presented as one holistic solution in the form of an optimised simulation pipeline. The results of analysis, experiments and case studies are used to derive a formula for relative spatial error that accounts for potential pathological cases. A formula for spatial error propagation is then derived by using the new knowledge of spatial error to extend numerical relative error propagation mathematics. Finally, analytical results are developed to provide a general mathematical expression for maximum simulation error and how it varies with distance from the origin and the number of mathematical operations performed. We conclude that the origin centric approach provides a general and optimal solution to spatial jitter. Along with changing the way one thinks about navigation, process guidelines and formulae developed in the study, the approach provides a new paradigm for positional computing. This paradigm can improve many aspects of computer simulation in areas such as entertainment, visualisation for education, industry, science, or training. Examples are: spatial scalability, the accuracy of motion, interaction and rendering; and the consistency and predictability of numerical computation in physics. This research also affords potential cost benefits through simplification of software design and code. These cost benefits come from some core techniques for minimising position dependent error, error propagation and also the simplifications and from new algorithms that flow naturally out of the core solution.

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Richer, Gaëlle. "Passage à l'échelle pour la visualisation interactive exploratoire de données : approches par abstraction et par déformation spatiale." Thesis, Bordeaux, 2019. http://www.theses.fr/2019BORD0264/document.

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La visualisation interactive est un outil essentiel pour l'exploration, la compréhension et l'analyse de données. L'exploration interactive efficace de jeux de données grands ou complexes présente cependant deux difficultés fondamentales. La première est visuelle et concerne les limitations de la perception et cognition humaine, ainsi que celles des écrans. La seconde est computationnelle et concerne les limitations de capacité mémoire ou de traitement des machines standards. Dans cette thèse, nous nous intéressons aux techniques de passage à l'échelle relativement à ces deux difficultés, pour plusieurs contextes d'application.Pour le passage à l'échelle visuelle, nous présentons une approche versatile de mise en évidence de sous-ensembles d'éléments par déformation spatiale appliquée aux vues multiples et une représentation abstraite et multi-/échelle de coordonnées parallèles. Sur les vues multiples, la déformation spatiale vise à remédier à la diminution de l'efficacité de la surbrillance lorsque les éléments graphiques sont de taille réduite. Sur les coordonnées parallèles, l'abstraction multi-échelle consiste à simplifier la représentation tout en permettant d'accéder interactivement au détail des données, en les pré-agrégeant à plusieurs niveaux de détail.Pour le passage à l'échelle computationnelle, nous étudions des approches de pré-calcul et de calcul à la volée sur des infrastructures distribuées permettant l'exploration de jeux de données de plus d'un milliard d'éléments en temps interactif. Nous présentons un système pour l'exploration de données multi-dimensionnelles dont les interactions et l'abstraction respectent un budget en nombre d'éléments graphiques qui, en retour, fournit une borne théorique sur les latences d'interactions dues au transfert réseau entre client et serveur. Avec le même objectif, nous comparons des stratégies de réduction de données géométrique pour la reconstruction de cartes de densité d'ensembles de points
Interactive visualization is helpful for exploring, understanding, and analyzing data. However, increasingly large and complex data challenges the efficiency of visualization systems, both visually and computationally. The visual challenge stems from human perceptual and cognitive limitations as well as screen space limitations while the computational challenge stems from the processing and memory limitations of standard computers.In this thesis, we present techniques addressing the two scalability issues for several interactive visualization applications.To address visual scalability requirements, we present a versatile spatial-distortion approach for linked emphasis on multiple views and an abstract and multi-scale representation based on parallel coordinates. Spatial distortion aims at alleviating the weakened emphasis effect of highlighting when applied to small-sized visual elements. Multiscale abstraction simplifies the representation while providing detail on demand by pre-aggregating data at several levels of detail.To address computational scalability requirements and scale data processing to billions of items in interactive times, we use pre-computation and real-time computation on a remote distributed infrastructure. We present a system for multi-/dimensional data exploration in which the interactions and abstract representation comply with a visual item budget and in return provides a guarantee on network-related interaction latencies. With the same goal, we compared several geometric reduction strategies for the reconstruction of density maps of large-scale point sets

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Tchappi, haman Igor. "Dynamic Multilevel and Holonic Model for the Simulation of a Large-Scale Complex System with Spatial Environment : Application to Road Traffic Simulation." Thesis, Bourgogne Franche-Comté, 2020. http://www.theses.fr/2020UBFCA004.

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De nos jours, avec l’émergence d’objets et de voitures connectés, les systèmes de trafic routier deviennent de plus en plus complexes et présentent des comportements hiérarchiques à plusieurs niveaux de détail. L'approche de modélisation multiniveaux est une approche appropriée pour représenter le trafic sous plusieurs perspectives. Les modèles multiniveaux constituent également une approche appropriée pour modéliser des systèmes complexes à grande échelle comme le trafic routier. Cependant, la plupart des modèles multiniveaux de trafic proposés dans la littérature sont statiques car ils utilisent un ensemble de niveaux de détail prédéfinis et ces représentations ne peuvent pas commuter pendant la simulation. De plus ces modèles multiniveaux considèrent généralement seulement deux niveaux de détail. Très peu de travaux se sont intéressés à la modélisation dynamique multiniveau de trafic.Cette thèse propose un modèle holonique multiniveau et dynamique du trafic à grande échelle.La commutation dynamique des niveaux de détail lors de l’exécution de la simulation permet d’adapter le modèle aux contraintes liées à la qualité des résultats ou aux ressources de calcul disponibles.La proposition étend l'algorithme DBSCAN dans le contexte des systèmes multi-agents holoniques. De plus, une méthodologie permettant la commutation dynamique entre les différents niveaux de détail est proposée. Des indicateurs multiniveaux basés sur l'écart type sont aussi proposés afin d'évaluer la cohérence des résultats de la simulation
Nowadays, with the emergence of connected objects and cars, road traffic systems become more and more complex and exhibit hierarchical behaviours at several levels of detail. The multilevel modeling approach is an appropriate approach to represent traffic from several perspectives. Multilevel models are also an appropriate approach to model large-scale complex systems such as road traffic. However, most of the multilevel models of traffic proposed in the literature are static because they use a set of predefined levels of detail and these representations cannot change during simulation. Moreover, these multilevel models generally consider only two levels of detail. Few works have been interested on the dynamic multilevel traffic modeling.This thesis proposes a holonic multilevel and dynamic traffic model for large scale traffic systems. The dynamic switching of the levels of detail during the execution of the simulation allows to adapt the model to the constraints related to the quality of the results or to the available computing resources.The proposal extends the DBSCAN algorithm in the context of holonic multi-agent systems. In addition, a methodology allowing a dynamic transition between the different levels of detail is proposed. Multilevel indicators based on standard deviation are also proposed in order to assess the consistency of the simulation results

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Lhuillier, Yves. "Architecture et programmation spatiale." Paris 11, 2005. http://www.theses.fr/2005PA112267.

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Les processeurs et multiprocesseurs actuels sont presque tous basés sur le paradigme Von Neumann. Grâce à ce paradigme, il est aisé de construire un processeur généraliste avec peu de transistors. L'accroissement en performance des processeurs Von Neumann a été majoritairement dû au formidable accroissement en fréquence qu'ont connu les technologies silicium. Dans la mesure où ces fréquences pourraient ne plus augmenter aussi vite qu'auparavant, beaucoup de travaux de recherche accordent aux architectures parallèles sur une même puce la capacité d'exploiter efficacement le nombre croissant de transistors. Dans cette thèse, nous introduisons d'abord un nouveau modèle de calcul, le "Blob Computing", combinant une architecture et un langage, tous les deux intrinsèquement conçus pour exploiter l'espace. A travers l'étude de ce paradigme, nous montrons que la remise en question de quelques principes à la base des machines Von Neumann permet potentiellement de dépasser certaines limitations majeures des architectures actuelles. Enfin, nous proposons une implémentation des concepts généraux du "Blob Computing" vers une architecture plus réaliste (processeurs multithreads). Nous attirons l'attention, grâce à cette implémentation, sur le fait que les efforts de recherche devront se concentrer sur l'obtention d'un équilibre entre le travail fourni par l'architecture, par le compilateur, et par l'utilisateur. En particulier, nous montrons qu'enrichir la sémantique parallèle passée par l'utilisateur dans son programme et donner à l'architecture le moyen d'exploiter cette sémantique constitue une voie prometteuse pour la scalabilité des futurs processeurs
Current processor and multiprocessor architectures are almost all based on the Von Neumann paradigm. Based on this paradigm, one can build a general-purpose computer using very few transistors. The performance improvement of Von Neumann processors was mainly due to the increase in clock frequency of silicon technologies. Because clock frequency may no longer increase as quickly, there is a growing consensus on on-chip concurrent architectures being a major route for the efficient exploitation of an increasing number of transistors. In this thesis, we first introduce a new computing model, the “Blob Computing” defining both an architecture and a language, that is intrinsically designed to exploit space. Through this model, we also want to outline that revisiting some of the principles of today's computing paradigm has the potential of overcoming major limitations of current architectures. Finaly, we propose an implementation of the “Blob Computing” main ideas on more traditional architectures (multithreaded processors). Thanks to this implementation, we advocate that research efforts should further focus on striking the right balance between architecture, compiler and user effort. Especially, we show that letting the user reasonably effortlessly pass information on program parallel properties and making the architecture ``aware'' of this additional information is a promising path for futur processors scalability

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Mrak, Marta. "Motion scalability for video coding with flexible spatio-temporal decompositions." Thesis, Queen Mary, University of London, 2007. http://qmro.qmul.ac.uk/xmlui/handle/123456789/1907.

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The research presented in this thesis aims to extend the scalability range of the wavelet-based video coding systems in order to achieve fully scalable coding with a wide range of available decoding points. Since the temporal redundancy regularly comprises the main portion of the global video sequence redundancy, the techniques that can be generally termed motion decorrelation techniques have a central role in the overall compression performance. For this reason the scalable motion modelling and coding are of utmost importance, and specifically, in this thesis possible solutions are identified and analysed. The main contributions of the presented research are grouped into two interrelated and complementary topics. Firstly a flexible motion model with rateoptimised estimation technique is introduced. The proposed motion model is based on tree structures and allows high adaptability needed for layered motion coding. The flexible structure for motion compensation allows for optimisation at different stages of the adaptive spatio-temporal decomposition, which is crucial for scalable coding that targets decoding on different resolutions. By utilising an adaptive choice of wavelet filterbank, the model enables high compression based on efficient mode selection. Secondly, solutions for scalable motion modelling and coding are developed. These solutions are based on precision limiting of motion vectors and creation of a layered motion structure that describes hierarchically coded motion. The solution based on precision limiting relies on layered bit-plane coding of motion vector values. The second solution builds on recently established techniques that impose scalability on a motion structure. The new approach is based on two major improvements: the evaluation of distortion in temporal Subbands and motion search in temporal subbands that finds the optimal motion vectors for layered motion structure. Exhaustive tests on the rate-distortion performance in demanding scalable video coding scenarios show benefits of application of both developed flexible motion model and various solutions for scalable motion coding.

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Herrou, Glenn. "Résolution Spatio-temporelle Adaptative pour un Codage à Faible Complexité des Formats Vidéo Émergents." Thesis, Rennes, INSA, 2019. http://www.theses.fr/2019ISAR0020.

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La standardisation du dernier format vidéo en date, appelé Ultra-High Definition TV (UHDTV), vise à améliorer la qualité l’expérience des utilisateurs en introduisant de nouvelles technologies telles que la 4K ou le High Frame-Rate (HFR). Cependant, ces améliorations multiplient la quantité de données à traiter avant transmission du signal par un facteur 8. En plus de ce nouveau format, les fournisseurs de contenu doivent aussi encoder les vidéos dans des formats et à des débits différents du fait de la grande variété des systèmes et réseaux utilisés par les consommateurs. SHVC, l’extension scalable du dernier standard de compression video High Efficiency Video Coding (HEVC) est une solution prometteuse pour adresser ces problématiques. En revanche, son architecture, très demandeuse en termes de calculs, atteint ses limites lors de l’encodage des nouveaux formats vidéo immersifs tels que le standard UHDTV.L’objectif de cette thèse est donc d’étudier des approches de codage scalables et légères basées sur l’adaptation de la résolution spatio-temporelle des vidéos. La première partie de cette thèse propose deux algorithmes de pré-traitement, utilisant respectivement des approches polyphase et ondelette basées image, afin de permettre la scalabilité spatiale avec une faible augmentation de la complexité.Ensuite, dans un second lieu, le design d’une architecture scalable à deux couches, plus conventionnelle, est étudié. Celle-ci est composée d’un encodeur HEVC standard dans la couche de base pour assurer la compatibilité avec les systèmes existants. Pour la couche d’amélioration, un encodeur basse complexité, se basant sur l’adaptation locale de la résolution spatiale, est proposé. Enfin, la dernière partie de cette thèse se focalise sur l’adaptation de la résolution spatio-temporelle. Un algorithme faisant varier la fréquence image est d’abord proposé. Cet algorithme est capable de détecter localement et de façon dynamique la fréquence image la plus basse n’introduisant pas d’artefacts visibles liés au mouvement. Les algorithmes de fréquence image variable et de résolution spatiale adaptative sont ensuite combinés afin d’offrir un codage scalable à faible complexité des contenus 4KHFR
The definition of the latest Ultra-High Definition TV (UHDTV) standard aims to increase the user’s quality of experience by introducing new video signal features such as 4K and High Frame-Rate (HFR). However, these new features multiply by a factor 8 the amount of data to be processed before transmission to the end user.In addition to this new format, broadcasters and Over-The-Top (OTT) content providers have to encode videos in different formats and at different bitrates due to the wide variety of devices with heterogeneous video format and network capacities used by consumers.SHVC, the scalable extension of the latest video coding standard High Efficiency Video Coding (HEVC) is a promising solution to address these issues but its computationally demanding architecture reaches its limit with the encoding and decoding of the data-heavy newly introduced immersive video features of the UHDTV video format.The objective of this thesis is thus to investigate lightweight scalable encoding approaches based on the adaptation of the spatio-temporal resolution. The first part of this document proposes two pre-processing tools, respectively using polyphase and wavelet frame-based approaches, to achieve spatial scalability with a slight complexity overhead.Then, the second part of this thesis addresses the design of a more conventional dual-layer scalable architecture using an HEVC encoder in the Base Layer (BL) for backward compatibility and a proposed low-complexity encoder, based on the local adaptation of the spatial resolution, for the Enhancement Layer (EL).Finally, the last part of this thesis investigates spatiotemporal resolution adaptation. A variable frame-rate algorithm is first proposed as pre-processing. This solution has been designed to locally and dynamically detect the lowest frame-rate that does not introduce visible motion artifacts. The proposed variable frame-rate and adaptive spatial resolution algorithms are then combined to offer a lightweight scalable coding of 4K HFR video contents

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Cortés, Rudyar. "Scalable location-temporal range query processing for structured peer-to-peer networks." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066106/document.

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Анотація:

La recherche et l'indexation de données en fonction d'une date ou d'une zone géographique permettent le partage et la découverte d'informations géolocalisées telles que l'on en trouve sur les réseaux sociaux comme Facebook, Flickr, ou Twitter. Cette réseau social connue sous le nom de Location Based Social Network (LBSN) s'applique à des millions d'utilisateurs qui partagent et envoient des requêtes ciblant des zones spatio-temporelles, permettant d'accéder à des données géolocalisées générées dans une zone géographique et dans un intervalle de temps donné. Un des principaux défis pour de telles applications est de fournir une architecture capable de traiter la multitude d'insertions et de requêtes spatio-temporelles générées par une grande quantité d'utilisateurs. A ces fins, les Tables de Hachage Distribué (DHT) et le paradigme Pair-à-Pair (P2P) sont autant de primitives qui forment la base pour les applications de grande envergure. Cependant, les DHTs sont mal adaptées aux requêtes ciblant des intervalles donnés; en effet, l'utilisation de fonctions de hachage sacrifie la localité des données au profit d'un meilleur équilibrage de la charge. Plusieurs solutions ajoutent le support de requêtes ciblant des ensembles aux DHTs. En revanche ces solutions ont tendance à générer un nombre de messages et une latence élevée pour des requêtes qui ciblent des intervalles. Cette thèse propose deux solutions à large échelle pour l'indexation des données géolocalisées
Indexing and retrieving data by location and time allows people to share and explore massive geotagged datasets observed on social networks such as Facebook, Flickr, and Twitter. This scenario known as a Location Based Social Network (LBSN) is composed of millions of users, sharing and performing location-temporal range queries in order to retrieve geotagged data generated inside a given geographic area and time interval. A key challenge is to provide a scalable architecture that allow to perform insertions and location-temporal range queries from a high number of users. In order to achieve this, Distributed Hash Tables (DHTs) and the Peer-to-Peer (P2P) computing paradigms provide a powerful building block for implementing large scale applications. However, DHTs are ill-suited for supporting range queries because the use of hash functions destroy data locality for the sake of load balance. Existing solutions that use a DHT as a building block allow to perform range queries. Nonetheless, they do not target location-temporal range queries and they exhibit poor performance in terms of query response time and message traffic. This thesis proposes two scalable solutions for indexing and retrieving geotagged data based on location and time

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Trocan, Maria. "Décompositions spatio-temporelles et allocation de débit en utilisant les coupures de graphe pour le codage vidéo scalable." Paris, ENST, 2007. http://www.theses.fr/2007ENST0032.

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Анотація:

Les progrès récents dans le domaine des schémas de codage vidéo par ondelettes ont permis l'apparition d'une nouvelle génération de codeurs vidéo scalables dont l'efficacité est comparable à celle des meilleurs codecs hybrides. Ces schémas sont qualifiés de t+2D et reposent sur l'utilisation d'une transformée en ondelettes appliquée le long du mouvement des images afin d exploiter leur redondance temporelle. Les sous-bandes résultantes sont alors décomposées spatialement et encodées par un codeur entropique. Grâce à la représentation multirésolution inhérente, les codeurs basés-ondelettes ont la capacité de fournir une description scalable d'un signal. Ceci représente la raison principale pour laquelle le choix du paradigme du codage lifting t+2D basé-ondelettes s'impose comme cadre conceptuel de développement pour les travaux dans cette thèse. L'objectif de ces travaux consiste en l'analyse et la conception d'un système de codage vidéo scalable. Dans un premier temps, nous nous intéressons à la construction et l'optimisation de nouvelles transformées temporelles compensées en mouvement, dans le but d'augmenter l'efficacité objective et subjective du codage. En outre, nous décrivons une meilleure représentation pour les sous-bandes temporelles en utilisant des décompositions spatiales anisotropes. Enfin, nous proposons une methode d'amélioration du codage entropique en concevant une solution basée sur la théorie des graphes, afin d'optimiser la minimisation du Lagrangien débit-distorsion
The recent progress in wavelet-based video coding led to the emergence of a new generation of scalable video schemes, whose performance is comparable to that of the best hybrid codecs. The t+2D subband coding methods exploit the temporal interframe redundancy by applying an open-loop temporal wavelet transform over the frames of a video sequence. The temporally-filtered subband frames are further spatially decomposed and entropy coded. Due to their inherent multiresolution signal representation, wavelet-based coding schemes have the potential to support temporal, spatial and SNR scalability. This is the main reason for chosing the scalable lifting-based wavelet-coding paradigm as the conceptual development framework for this thesis work. The objective of this thesis consists of the analysis and design of an efficient scalable video-coding system. In a first time, we are interested in the construction and optimization of motion-compensated temporal coding schemes, in order to enhance both the objective and subjective coding quality. Moreover, we describe a better representation of the temporal subbands by using anisotropic spatial decompositions. Finally, we improve the entropy coding by designing a graph-cut solvable energy functional for the Lagrangian rate-distortion optimization problem

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Книги з теми "Spatial scalability"

D, Joslin Ronald, Zubair Mohammad, and Langley Research Center, eds. Scalability study of parallel spatial direct numerical simulation code on IBM SP1 parallel supercomputer. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1994.

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Частини книг з теми "Spatial scalability"

Martin, Ben, and Peter Eklund. "Spatial Indexing for Scalability in FCA." In Formal Concept Analysis, 205–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11671404_14.

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Lai, Wei, Xiao-Dong Gu, Ren-Hua Wang, Li-Rong Dai, and Hong-Jiang Zhang. "Perceptual Video Streaming by Adaptive Spatial-temporal Scalability." In Advances in Multimedia Information Processing - PCM 2004, 431–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30542-2_53.

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Deknudt, Christophe, Franc̨ois-Xavier Coudoux, Patrick Corlay, Marc Gazalet, and Mohamed Gharbi. "Efficient Low Complexity SVC Video Transrater with Spatial Scalability." In Advanced Concepts for Intelligent Vision Systems, 1–12. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02895-8_1.

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Pezenka, Lukas, Stefan Wolfsberger, and Katja Bühler. "Employing Spatial Indexing for Flexibility and Scalability in Brain Biopsy Planning." In Bildverarbeitung für die Medizin 2018, 145–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-56537-7_45.

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Manogaran, Ugenteraan, Ya Ping Wong, and Boon Yian Ng. "Survey on Capsule Network’s Depth Scalability and Learned Feature Spatial Relationships Retention." In Lecture Notes in Networks and Systems, 165–82. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98015-3_11.

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Wang, Ren-Jie, Yan-Ting Jiang, Jiunn-Tsair Fang, and Pao-Chi Chang. "Quality Estimation for H.264/SVC Inter-layer Residual Prediction in Spatial Scalability." In Advances in Image and Video Technology, 252–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25346-1_23.

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Zhang, Dongdong, Jizheng Xu, Feng Wu, Wenjun Zhang, and Hongkai Xiong. "A Cross-Resolution Leaky Prediction Scheme for In-Band Wavelet Video Coding with Spatial Scalability." In Advances in Multimedia Information Processing - PCM 2005, 156–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11581772_14.

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Shead, T. M., I. K. Tezaur, W. L. Davis IV, M. L. Carlson, D. M. Dunlavy, E. J. Parish, P. J. Blonigan, J. Tencer, F. Rizzi, and H. Kolla. "A Novel In Situ Machine Learning Framework for Intelligent Data Capture and Event Detection." In Lecture Notes in Energy, 53–87. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-16248-0_3.

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AbstractWe present a novel framework for automatically detecting spatial and temporal events of interest in situ while running high performance computing (HPC) simulations. The new framework – composed from signature, measure, and decision building blocks with well-defined semantics – is tailored for parallel and distributed computing, has bounded communication and storage requirements, is generalizable to a variety of applications, and operates in an unsupervised fashion. We demonstrate the efficacy of our framework on several cases spanning scientific domains and applications of event detection: optimized input/output (I/O) in computational fluid dynamics simulations, detecting events that can lead to irreversible climate changes in simulations of polar ice sheets, and identifying optimal space-time subregions for projection-based model reduction. Additionally, we demonstrate the scalability of our framework using a HPC combustion application on the Cori supercomputer at the National Energy Research Scientific Computing Center (NERSC).

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Du, Dawei, and Dan Simon. "Biogeography-Based Optimization for Large Scale Combinatorial Problems." In Efficiency and Scalability Methods for Computational Intellect, 197–217. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-3942-3.ch010.

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Biogeography-based optimization (BBO) is a recently-developed heuristic algorithm that has shown impressive performance and efficiency over many standard benchmarks. The application of BBO is still limited because it was only developed four years ago. The objective of this chapter is to expand the application of BBO to large scale combinatorial problems. This chapter addresses the solution of combinatorial problems based on BBO combined with five techniques: (1) nearest neighbor algorithm (NNA), (2) crossover methods designed for traveling salesman problems (TSPs), (3) local optimization methods, (4) greedy methods, and (5) density-based spatial clustering of applications with noise (DBSCAN). This chapter also provides a discussion about the advantages and disadvantages for each of these five techniques when used with BBO, and describes the construction of a combinatorial solver based on BBO. In the end, a framework is proposed for large scale combinatorial problems based on hybrid BBO. Based on four benchmark problems, the experimental results demonstrate the quality and efficiency of our framework. On average, the algorithm reduces costs by over 69% for a 2152-city TSP compared to other methods: genetic algorithm (GA), ant colony optimization (ACO), nearest neighbor algorithm (NNA), and simulated annealing (SA). Convergence time for the algorithm is only 28.56 sec on a 1.73-GHz quad core PC with 6 GB of RAM . The algorithm also demonstrated good results for small and medium sized problems such as ulysses16 (16-city TSP, where we obtained the best performance), st70 (70-city TSP, where the second best performance was obtained), and rat575 (575-city TSP, where the second best performance was obtained).

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KC, Ujjwal, and Jagannath Aryal. "Leveraging a wildfire risk prediction metric with spatial clustering." In Advances in Forest Fire Research 2022, 289–93. Imprensa da Universidade de Coimbra, 2022. http://dx.doi.org/10.14195/978-989-26-2298-9_45.

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Fire authorities have started widely using operational fire simulations for effective wildfire management. These fire simulation outputs, when aggregated on a massive scale, create an opportunity to apply the evolving data-driven approach to closely estimate wildfire risks even without running computationally expensive simulations. We explored this opportunity in one of our previous works where we proposed a probability-based risk metric that gives a series of probability values for a fire starting at a start location under a given weather condition, to fall into different risk categories. The metric considered each fire start location as a unique entity, which could face scalability issues when the metric is used for a larger geographic area and make the metric hugely compute-intensive. In this work, we investigate if the spatial clustering of fire start locations based on historical fire areas can address the issue without significantly compromising the accuracy of the metric. Additionally, as spatial clusters are significantly fewer than fire start locations in a geographic area, spatial clustering can further reduce the overall computational requirements of the metric with a rational compromise of accuracy.

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Тези доповідей конференцій з теми "Spatial scalability"

Segall, Andrew, and Aggelos Katsaggelos. "Resampling for Spatial Scalability." In 2006 International Conference on Image Processing. IEEE, 2006. http://dx.doi.org/10.1109/icip.2006.312364.

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Francois, Edouard, and Jerome Vieron. "Extended Spatial Scalability : A Generalization of Spatial Scalability for Non Dyadic Configurations." In 2006 International Conference on Image Processing. IEEE, 2006. http://dx.doi.org/10.1109/icip.2006.312363.

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Hu, Qingwen, and Sethuraman Panchanathan. "Spatial scalability in compressed domain." In Electronic Imaging: Science & Technology, edited by Vasudev Bhaskaran, Frans Sijstermans, and Sethuraman Panchanathan. SPIE, 1996. http://dx.doi.org/10.1117/12.235445.

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"On improving MPEG spatial scalability." In Proceedings of 7th IEEE International Conference on Image Processing. IEEE, 2000. http://dx.doi.org/10.1109/icip.2000.5286958.

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Anreddy, Sujan, Song Zhang, Andrew Mercer, Jamie Dyer, and J. Edward Swan. "Visual scalability of spatial ensemble uncertainty." In 2015 IEEE Conference on Visual Analytics Science and Technology (VAST). IEEE, 2015. http://dx.doi.org/10.1109/vast.2015.7347671.

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Chavarrias, M., F. Pescador, F. Jaureguizar, E. Juarez, and M. J. Garrido. "3D videoconferencing system using spatial scalability." In 2012 IEEE International Conference on Consumer Electronics (ICCE). IEEE, 2012. http://dx.doi.org/10.1109/icce.2012.6161789.

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Yao, Wei, Zhengguo Li, and Susanto Rahardja. "Balanced Inter-Layer Prediction for Combined Coarse Granular Scalability and Spatial Scalability." In 2007 IEEE International Symposium on Circuits and Systems. IEEE, 2007. http://dx.doi.org/10.1109/iscas.2007.378012.

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Jin, Xin, Guangxi Zhu, and King Ngi Ngan. "Complexity-Controllable Video Coding with Spatial Scalability." In MILCOM 2007 - IEEE Military Communications Conference. IEEE, 2007. http://dx.doi.org/10.1109/milcom.2007.4455017.

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Junjian Quan, Miska M. Hannuksela, and Houqiang Li. "Asymmetric spatial scalability in stereoscopic video coding." In 2011 3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON 2011). IEEE, 2011. http://dx.doi.org/10.1109/3dtv.2011.5877219.

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Li, Z., S. Rahardja, X. Lin, and Wei Yao. "Customer Adaptive Combined SNR and Spatial Scalability." In 2005 IEEE 7th Workshop on Multimedia Signal Processing. IEEE, 2005. http://dx.doi.org/10.1109/mmsp.2005.248635.

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