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Author: Rui Li Publisher: ISBN: Category : Languages : en Pages : 246
Book Description
Abstract: The goal of this work is to learn a parsimonious and informative representation for high-dimensional time series. Conceptually, this comprises two distinct yet tightly coupled tasks: learning a low-dimensional manifold and modeling the dynamical process. These two tasks have a complementary relationship as the temporal constraints provide valuable neighborhood information for dimensionality reduction and conversely, the low-dimensional space allows dynamics to be learnt efficiently. Solving these two tasks simultaneously allows important information to be exchanged mutually. If nonlinear models are required to capture the rich complexity of time series, then the learning problem becomes harder as the nonlinearities in both tasks are coupled. The proposed solution approximates the nonlinear manifold and dynamics using piecewise linear models. The interactions among the linear models are captured in a graphical model. The model structure setup and parameter learning are done using a variational Bayesian approach, which enables automatic Bayesian model structure selection, hence solving the problem of over-fitting. By exploiting the model structure, efficient inference and learning algorithms are obtained without oversimplifying the model of the underlying dynamical process. Evaluation of the proposed framework with competing approaches is conducted in three sets of experiments: dimensionality reduction and reconstruction using synthetic time series, video synthesis using a dynamic texture database, and human motion synthesis, classification and tracking on a benchmark data set. In all experiments, the proposed approach provides superior performance.
Author: Rui Li Publisher: ISBN: Category : Languages : en Pages : 246
Book Description
Abstract: The goal of this work is to learn a parsimonious and informative representation for high-dimensional time series. Conceptually, this comprises two distinct yet tightly coupled tasks: learning a low-dimensional manifold and modeling the dynamical process. These two tasks have a complementary relationship as the temporal constraints provide valuable neighborhood information for dimensionality reduction and conversely, the low-dimensional space allows dynamics to be learnt efficiently. Solving these two tasks simultaneously allows important information to be exchanged mutually. If nonlinear models are required to capture the rich complexity of time series, then the learning problem becomes harder as the nonlinearities in both tasks are coupled. The proposed solution approximates the nonlinear manifold and dynamics using piecewise linear models. The interactions among the linear models are captured in a graphical model. The model structure setup and parameter learning are done using a variational Bayesian approach, which enables automatic Bayesian model structure selection, hence solving the problem of over-fitting. By exploiting the model structure, efficient inference and learning algorithms are obtained without oversimplifying the model of the underlying dynamical process. Evaluation of the proposed framework with competing approaches is conducted in three sets of experiments: dimensionality reduction and reconstruction using synthetic time series, video synthesis using a dynamic texture database, and human motion synthesis, classification and tracking on a benchmark data set. In all experiments, the proposed approach provides superior performance.
Author: Kostas Daniilidis Publisher: Springer ISBN: 3642155588 Category : Computers Languages : en Pages : 833
Book Description
The 2010 edition of the European Conference on Computer Vision was held in Heraklion, Crete. The call for papers attracted an absolute record of 1,174 submissions. We describe here the selection of the accepted papers: Thirty-eight area chairs were selected coming from Europe (18), USA and Canada (16), and Asia (4). Their selection was based on the following criteria: (1) Researchers who had served at least two times as Area Chairs within the past two years at major vision conferences were excluded; (2) Researchers who served as Area Chairs at the 2010 Computer Vision and Pattern Recognition were also excluded (exception: ECCV 2012 Program Chairs); (3) Minimization of overlap introduced by Area Chairs being former student and advisors; (4) 20% of the Area Chairs had never served before in a major conference; (5) The Area Chair selection process made all possible efforts to achieve a reasonable geographic distribution between countries, thematic areas and trends in computer vision. Each Area Chair was assigned by the Program Chairs between 28–32 papers. Based on paper content, the Area Chair recommended up to seven potential reviewers per paper. Such assignment was made using all reviewers in the database including the conflicting ones. The Program Chairs manually entered the missing conflict domains of approximately 300 reviewers. Based on the recommendation of the Area Chairs, three reviewers were selected per paper (with at least one being of the top three suggestions), with 99.
Author: José M. Ferrández Publisher: Springer Science & Business Media ISBN: 364221343X Category : Computers Languages : en Pages : 588
Book Description
The two volumes, LNCS 6686 resp. LNCS 6687, constitute the refereed proceedings of the 4th International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2011, held in La Palma, Canary Islands, Spain, in May/June 2011. The 108 revised full papers presented in LNCS 6686 resp. LNCS 6687 were carefully reviewed and selected from numerous submissions. The first part, LNCS 6686, entitled "Foundations on Natural and Artificial Computation", includes all the contributions mainly related to the methodological, conceptual, formal, and experimental developments in the fields of neurophysiology and cognitive science. The second part, LNCS 6687, entitled "New Challenges on Bioinspired Applications", contains the papers related to bioinspired programming strategies and all the contributions related to the computational solutions to engineering problems in different application domains, specially Health applications, including the CYTED ``Artificial and Natural Computation for Health'' (CANS) research network papers.
Author: Hideyuki Nakashima Publisher: Springer Science & Business Media ISBN: 0387938087 Category : Computers Languages : en Pages : 1290
Book Description
Our homes anticipate when we want to wake up. Our computers predict what music we want to buy. Our cars adapt to the way we drive. In today’s world, even washing machines, rice cookers and toys have the capability of autonomous decision-making. As we grow accustomed to computing power embedded in our surroundings, it becomes clear that these ‘smart environments’, with a number of devices controlled by a coordinating system capable of ‘ambient intelligence’, will play an ever larger role in our lives. This handbook provides readers with comprehensive, up-to-date coverage in what is a key technological field. . Systematically dealing with each aspect of ambient intelligence and smart environments, the text covers everything, from visual information capture and human/computer interaction to multi-agent systems, network use of sensor data, and building more rationality into artificial systems. The book also details a wide range of applications, examines case studies of recent major projects from around the world, and analyzes both the likely impact of the technology on our lives, and its ethical implications. With a wide variety of separate disciplines all conducting research relevant to this field, this handbook encourages collaboration between disparate researchers by setting out the fundamental concepts from each area that are relevant to ambient intelligence and smart environments, providing a fertile soil in which ground-breaking new work candevelop.
Author: David Forsyth Publisher: Springer ISBN: 3540886885 Category : Computers Languages : en Pages : 869
Book Description
The four-volume set comprising LNCS volumes 5302/5303/5304/5305 constitutes the refereed proceedings of the 10th European Conference on Computer Vision, ECCV 2008, held in Marseille, France, in October 2008. The 243 revised papers presented were carefully reviewed and selected from a total of 871 papers submitted. The four books cover the entire range of current issues in computer vision. The papers are organized in topical sections on recognition, stereo, people and face recognition, object tracking, matching, learning and features, MRFs, segmentation, computational photography and active reconstruction.
Author: Ignacio Rojas Publisher: Springer ISBN: 3319969447 Category : Business & Economics Languages : en Pages : 332
Book Description
This book presents selected peer-reviewed contributions from the International Work-Conference on Time Series, ITISE 2017, held in Granada, Spain, September 18-20, 2017. It discusses topics in time series analysis and forecasting, including advanced mathematical methodology, computational intelligence methods for time series, dimensionality reduction and similarity measures, econometric models, energy time series forecasting, forecasting in real problems, online learning in time series as well as high-dimensional and complex/big data time series. The series of ITISE conferences provides a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing computer science, mathematics, statistics and econometrics.
Author: Stephane Ploix Publisher: Springer Nature ISBN: 303076477X Category : Technology & Engineering Languages : en Pages : 627
Book Description
This book exemplifies how smart buildings have a crucial role to play for the future of energy. The book investigates what already exists in regards to technologies, approaches and solutions both with a scientific and technological point of view. The authors cover solutions for mirroring and tracing human activities, optimal strategies to configure home settings, and generating explanations and persuasive dashboards to get occupants better committed in their home energy managements. Solutions are adapted from the fields of Internet of Things, physical modeling, optimization, machine learning and applied artificial intelligence. Practical applications are given throughout.
Author: Thomas B. Moeslund Publisher: Springer Science & Business Media ISBN: 0857299972 Category : Computers Languages : en Pages : 633
Book Description
This unique text/reference provides a coherent and comprehensive overview of all aspects of video analysis of humans. Broad in coverage and accessible in style, the text presents original perspectives collected from preeminent researchers gathered from across the world. In addition to presenting state-of-the-art research, the book reviews the historical origins of the different existing methods, and predicts future trends and challenges. Features: with a Foreword by Professor Larry Davis; contains contributions from an international selection of leading authorities in the field; includes an extensive glossary; discusses the problems associated with detecting and tracking people through camera networks; examines topics related to determining the time-varying 3D pose of a person from video; investigates the representation and recognition of human and vehicular actions; reviews the most important applications of activity recognition, from biometrics and surveillance, to sports and driver assistance.
Author: Michal Haindl Publisher: Springer Science & Business Media ISBN: 1447149025 Category : Computers Languages : en Pages : 304
Book Description
This book surveys the state of the art in multidimensional, physically-correct visual texture modeling. Features: reviews the entire process of texture synthesis, including material appearance representation, measurement, analysis, compression, modeling, editing, visualization, and perceptual evaluation; explains the derivation of the most common representations of visual texture, discussing their properties, advantages, and limitations; describes a range of techniques for the measurement of visual texture, including BRDF, SVBRDF, BTF and BSSRDF; investigates the visualization of textural information, from texture mapping and mip-mapping to illumination- and view-dependent data interpolation; examines techniques for perceptual validation and analysis, covering both standard pixel-wise similarity measures and also methods of visual psychophysics; reviews the applications of visual textures, from visual scene analysis in medical applications, to high-quality visualizations in the automotive industry.
Author: Boris P. Bezruchko Publisher: Springer Science & Business Media ISBN: 3642126014 Category : Science Languages : en Pages : 416
Book Description
Mathematical modelling is ubiquitous. Almost every book in exact science touches on mathematical models of a certain class of phenomena, on more or less speci?c approaches to construction and investigation of models, on their applications, etc. As many textbooks with similar titles, Part I of our book is devoted to general qu- tions of modelling. Part II re?ects our professional interests as physicists who spent much time to investigations in the ?eld of non-linear dynamics and mathematical modelling from discrete sequences of experimental measurements (time series). The latter direction of research is known for a long time as “system identi?cation” in the framework of mathematical statistics and automatic control theory. It has its roots in the problem of approximating experimental data points on a plane with a smooth curve. Currently, researchers aim at the description of complex behaviour (irregular, chaotic, non-stationary and noise-corrupted signals which are typical of real-world objects and phenomena) with relatively simple non-linear differential or difference model equations rather than with cumbersome explicit functions of time. In the second half of the twentieth century, it has become clear that such equations of a s- ?ciently low order can exhibit non-trivial solutions that promise suf?ciently simple modelling of complex processes; according to the concepts of non-linear dynamics, chaotic regimes can be demonstrated already by a third-order non-linear ordinary differential equation, while complex behaviour in a linear model can be induced either by random in?uence (noise) or by a very high order of equations.
Author: Rui Li
Author: Rui Li
Author: Kostas Daniilidis
Author: José M. Ferrández
Author: Hideyuki Nakashima
Author: David Forsyth
Author: Ignacio Rojas
Author: Stephane Ploix
Author: Thomas B. Moeslund
Author: Michal Haindl
Author: Boris P. Bezruchko