A Bayesian Approach to Learning 3D Representations of Dynamic Environments PDF Download
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Author: Ralf Kästner
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Ralf Kästner
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Oussama Khatib
Publisher: Springer
ISBN: 3642285724
Category : Technology & Engineering
Languages : en
Pages : 919
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Book Description
Incorporating papers from the 12th International Symposium on Experimental Robotics (ISER), December 2010, this book examines the latest advances across the various fields of robotics. Offers insights on both theoretical concepts and experimental results.
Author: Joaquim Filipe
Publisher: Springer
ISBN: 3319264532
Category : Technology & Engineering
Languages : en
Pages : 324
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Book Description
The present book includes a set of selected extended papers from the 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2014), held in Vienna, Austria, from 1 to 3 September 2014. The conference brought together researchers, engineers and practitioners interested in the application of informatics to Control, Automation and Robotics. Four simultaneous tracks will be held, covering Intelligent Control Systems, Optimization, Robotics, Automation, Signal Processing, Sensors, Systems Modelling and Control, and Industrial Engineering, Production and Management. Informatics applications are pervasive in many areas of Control, Automation and Robotics. ICINCO 2014 received 301 submissions, from 49 countries, in all continents. After a double blind paper review performed by the Program Committee, 20% were accepted as full papers and thus selected for oral presentation. Additional papers were accepted as short papers and posters. A further selection was made after the Conference, based also on the assessment of presentation quality and audience interest, so that this book includes the extended and revised versions of the very best papers of ICINCO 2014. Commitment to high quality standards is a major concern of ICINCO that will be maintained in the next editions, considering not only the stringent paper acceptance ratios but also the quality of the program committee, keynote lectures, participation level and logistics.
Author: Péter Galambos
Publisher: Springer Nature
ISBN: 3031196503
Category : Computers
Languages : en
Pages : 241
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Book Description
This volume constitutes the papers of two workshops which were held in conjunctionwith the First International Conference on Robotics, Computer Vision and Intelligent Systems,ROBOVIS 2020, Virtual Event, in November 4-6, 2020 and Second International Conference on Robotics, Computer Vision and Intelligent Systems,ROBOVIS 2021, Virtual Event, in October 25-27, 2021. The 11 revised full papers presented in this book were carefully reviewed and selectedfrom 53 submissions.
Author: Csaba Benedek
Publisher: Springer Nature
ISBN: 3030836541
Category : Mathematics
Languages : en
Pages : 208
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Book Description
This book deals with selected problems of machine perception, using various 2D and 3D imaging sensors. It proposes several new original methods, and also provides a detailed state-of-the-art overview of existing techniques for automated, multi-level interpretation of the observed static or dynamic environment. To ensure a sound theoretical basis of the new models, the surveys and algorithmic developments are performed in well-established Bayesian frameworks. Low level scene understanding functions are formulated as various image segmentation problems, where the advantages of probabilistic inference techniques such as Markov Random Fields (MRF) or Mixed Markov Models are considered. For the object level scene analysis, the book mainly relies on the literature of Marked Point Process (MPP) approaches, which consider strong geometric and prior interaction constraints in object population modeling. In particular, key developments are introduced in the spatial hierarchical decomposition of the observed scenarios, and in the temporal extension of complex MRF and MPP models. Apart from utilizing conventional optical sensors, case studies are provided on passive radar (ISAR) and Lidar-based Bayesian environment perception tasks. It is shown, via several experiments, that the proposed contributions embedded into a strict mathematical toolkit can significantly improve the results in real world 2D/3D test images and videos, for applications in video surveillance, smart city monitoring, autonomous driving, remote sensing, and optical industrial inspection.
Author: Xiaoyi Jiang
Publisher: Springer
ISBN: 3642403034
Category : Computers
Languages : en
Pages : 214
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Book Description
This book constitutes the refereed proceedings of the International Workshop on Depth Image Analysis, held in conjunction with ICPR 2012 in Japan in November 2012. The 16 revised full papers presented at the workshop were carefully reviewed and selected from 27 submissions and are complemented with 3 invited papers that were also peer-reviewed. The papers are organized in topical sections on acquisition and modeling of depth data, processing and analysis of depth data, applications, and ICPR contest.
Author: Mike West
Publisher: Springer
ISBN: 9781475770988
Category : Mathematics
Languages : en
Pages : 0
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Book Description
This text is concerned with Bayesian learning, inference and forecasting in dynamic environments. We describe the structure and theory of classes of dynamic models and their uses in forecasting and time series analysis. The principles, models and methods of Bayesian forecasting and time - ries analysis have been developed extensively during the last thirty years. Thisdevelopmenthasinvolvedthoroughinvestigationofmathematicaland statistical aspects of forecasting models and related techniques. With this has come experience with applications in a variety of areas in commercial, industrial, scienti?c, and socio-economic ?elds. Much of the technical - velopment has been driven by the needs of forecasting practitioners and applied researchers. As a result, there now exists a relatively complete statistical and mathematical framework, presented and illustrated here. In writing and revising this book, our primary goals have been to present a reasonably comprehensive view of Bayesian ideas and methods in m- elling and forecasting, particularly to provide a solid reference source for advanced university students and research workers.
Author: Eric Parent
Publisher: CRC Press
ISBN: 1584889195
Category : Mathematics
Languages : en
Pages : 429
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Book Description
Making statistical modeling and inference more accessible to ecologists and related scientists, Introduction to Hierarchical Bayesian Modeling for Ecological Data gives readers a flexible and effective framework to learn about complex ecological processes from various sources of data. It also helps readers get started on building their own statistical models. The text begins with simple models that progressively become more complex and realistic through explanatory covariates and intermediate hidden states variables. When fitting the models to data, the authors gradually present the concepts and techniques of the Bayesian paradigm from a practical point of view using real case studies. They emphasize how hierarchical Bayesian modeling supports multidimensional models involving complex interactions between parameters and latent variables. Data sets, exercises, and R and WinBUGS codes are available on the authors’ website. This book shows how Bayesian statistical modeling provides an intuitive way to organize data, test ideas, investigate competing hypotheses, and assess degrees of confidence of predictions. It also illustrates how conditional reasoning can dismantle a complex reality into more understandable pieces. As conditional reasoning is intimately linked with Bayesian thinking, considering hierarchical models within the Bayesian setting offers a unified and coherent framework for modeling, estimation, and prediction.
Author: Mevin B. Hooten
Publisher: CRC Press
ISBN: 0429513372
Category : Science
Languages : en
Pages : 591
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Book Description
Bringing Bayesian Models to Life empowers the reader to extend, enhance, and implement statistical models for ecological and environmental data analysis. We open the black box and show the reader how to connect modern statistical models to computer algorithms. These algorithms allow the user to fit models that answer their scientific questions without needing to rely on automated Bayesian software. We show how to handcraft statistical models that are useful in ecological and environmental science including: linear and generalized linear models, spatial and time series models, occupancy and capture-recapture models, animal movement models, spatio-temporal models, and integrated population-models. Features: R code implementing algorithms to fit Bayesian models using real and simulated data examples. A comprehensive review of statistical models commonly used in ecological and environmental science. Overview of Bayesian computational methods such as importance sampling, MCMC, and HMC. Derivations of the necessary components to construct statistical algorithms from scratch. Bringing Bayesian Models to Life contains a comprehensive treatment of models and associated algorithms for fitting the models to data. We provide detailed and annotated R code in each chapter and apply it to fit each model we present to either real or simulated data for instructional purposes. Our code shows how to create every result and figure in the book so that readers can use and modify it for their own analyses. We provide all code and data in an organized set of directories available at the authors' websites.
Author: J.C. Augusto
Publisher: IOS Press
ISBN: 1614994110
Category : Computers
Languages : en
Pages : 316
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Book Description
Advances in the engineering of sensing and acting capabilities, distributed in a wide range of specialized devices nowadays, provide an opportunity for the fundamental advances in computer science made in the past few decades to impact our daily lives. Sensors/actuators deployed in a physical space – a house, an office, a classroom, a car, a street – facilitate a link between an automated decision-making system and a technologically-enriched space. The Intelligent Environment, a digital environment that supports people in their daily lives, is a very active area of research which is attracting an increasing number of professionals (both in academia and industry) worldwide. The prestigious 10th International Conference on Intelligent Environments (IE’14) is focused on the development of advanced Intelligent Environments and stimulates the discussion on several specific topics that are crucial to the future of the area. This volume is the combined proceedings of the workshops co-located with IE’14: 9th Workshop on Artificial Intelligence Techniques for Ambient Intelligence (AITAmI’14); 2nd International Workshop on Applications of Affective Computing in Intelligent Environments (ACIE’14); 3rd edition of the Workshop on Future Intelligent Educational Environments (WOFIEE’14); 2nd Workshop on Cloud-of-Things 2014 (CoT’14); 3rd International Workshop on the Reliability of Intelligent Environments (WoRIE 2014); 4th Workshop on Creative Science 2014 (CS’14); and 1st Workshop on Hyperrealistic Intelligent Environments 2014 (HyperRealitIE’14). This book offers an overview of the latest developments in key areas of the development of Intelligent Environments.
