Multimodal Scene Understanding

Multimodal Scene Understanding
Author: Michael Yang,Bodo Rosenhahn,Vittorio Murino
Publsiher: Academic Press
Total Pages: 422
Release: 2019-07-16
Genre: Computers
ISBN: 9780128173596

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Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and describes the role and approaches of multi-sensory data and multi-modal deep learning. The book is ideal for researchers from the fields of computer vision, remote sensing, robotics, and photogrammetry, thus helping foster interdisciplinary interaction and collaboration between these realms. Researchers collecting and analyzing multi-sensory data collections – for example, KITTI benchmark (stereo+laser) - from different platforms, such as autonomous vehicles, surveillance cameras, UAVs, planes and satellites will find this book to be very useful. Contains state-of-the-art developments on multi-modal computing Shines a focus on algorithms and applications Presents novel deep learning topics on multi-sensor fusion and multi-modal deep learning

Multimodal Computational Attention for Scene Understanding and Robotics

Multimodal Computational Attention for Scene Understanding and Robotics
Author: Boris Schauerte
Publsiher: Springer
Total Pages: 203
Release: 2016-05-11
Genre: Technology & Engineering
ISBN: 9783319337968

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This book presents state-of-the-art computational attention models that have been successfully tested in diverse application areas and can build the foundation for artificial systems to efficiently explore, analyze, and understand natural scenes. It gives a comprehensive overview of the most recent computational attention models for processing visual and acoustic input. It covers the biological background of visual and auditory attention, as well as bottom-up and top-down attentional mechanisms and discusses various applications. In the first part new approaches for bottom-up visual and acoustic saliency models are presented and applied to the task of audio-visual scene exploration of a robot. In the second part the influence of top-down cues for attention modeling is investigated.

Multimodal Computational Attention for Scene Understanding

Multimodal Computational Attention for Scene Understanding
Author: Boris Schauerte
Publsiher: Unknown
Total Pages: 135
Release: 2014
Genre: Electronic Book
ISBN: OCLC:899182558

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Machine Learning for Multimodal Interaction

Machine Learning for Multimodal Interaction
Author: Andrei Popescu-Belis,Steve Renals,Hervé Bourlard
Publsiher: Springer
Total Pages: 308
Release: 2008-02-22
Genre: Computers
ISBN: 9783540781554

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This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Machine Learning for Multimodal Interaction, MLMI 2007, held in Brno, Czech Republic, in June 2007. The 25 revised full papers presented together with 1 invited paper were carefully selected during two rounds of reviewing and revision from 60 workshop presentations. The papers are organized in topical sections on multimodal processing, HCI, user studies and applications, image and video processing, discourse and dialogue processing, speech and audio processing, as well as the PASCAL speech separation challenge.

Real time Multimodal Semantic Scene Understanding for Autonomous UGV Navigation

Real time Multimodal Semantic Scene Understanding for Autonomous UGV Navigation
Author: Yifei Zhang
Publsiher: Unknown
Total Pages: 114
Release: 2021
Genre: Electronic Book
ISBN: OCLC:1240393234

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Robust semantic scene understanding is challenging due to complex object types, as well as environmental changes caused by varying illumination and weather conditions. This thesis studies the problem of deep semantic segmentation with multimodal image inputs. Multimodal images captured from various sensory modalities provide complementary information for complete scene understanding. We provided effective solutions for fully-supervised multimodal image segmentation and few-shot semantic segmentation of the outdoor road scene. Regarding the former case, we proposed a multi-level fusion network to integrate RGB and polarimetric images. A central fusion framework was also introduced to adaptively learn the joint representations of modality-specific features and reduce model uncertainty via statistical post-processing.In the case of semi-supervised semantic scene understanding, we first proposed a novel few-shot segmentation method based on the prototypical network, which employs multiscale feature enhancement and the attention mechanism. Then we extended the RGB-centric algorithms to take advantage of supplementary depth cues. Comprehensive empirical evaluations on different benchmark datasets demonstrate that all the proposed algorithms achieve superior performance in terms of accuracy as well as demonstrating the effectiveness of complementary modalities for outdoor scene understanding for autonomous navigation.

Active Vision for Scene Understanding

Active Vision for Scene Understanding
Author: Grotz, Markus
Publsiher: KIT Scientific Publishing
Total Pages: 204
Release: 2021-12-21
Genre: Computers
ISBN: 9783731511014

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Visual perception is one of the most important sources of information for both humans and robots. A particular challenge is the acquisition and interpretation of complex unstructured scenes. This work contributes to active vision for humanoid robots. A semantic model of the scene is created, which is extended by successively changing the robot's view in order to explore interaction possibilities of the scene.

2016 International Symposium on Experimental Robotics

2016 International Symposium on Experimental Robotics
Author: Dana Kulić,Yoshihiko Nakamura,Oussama Khatib,Gentiane Venture
Publsiher: Springer
Total Pages: 856
Release: 2017-03-20
Genre: Technology & Engineering
ISBN: 9783319501154

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Experimental Robotics XV is the collection of papers presented at the International Symposium on Experimental Robotics, Roppongi, Tokyo, Japan on October 3-6, 2016. 73 scientific papers were selected and presented after peer review. The papers span a broad range of sub-fields in robotics including aerial robots, mobile robots, actuation, grasping, manipulation, planning and control and human-robot interaction, but shared cutting-edge approaches and paradigms to experimental robotics. The readers will find a breadth of new directions of experimental robotics. The International Symposium on Experimental Robotics is a series of bi-annual symposia sponsored by the International Foundation of Robotics Research, whose goal is to provide a forum dedicated to experimental robotics research. Robotics has been widening its scientific scope, deepening its methodologies and expanding its applications. However, the significance of experiments remains and will remain at the center of the discipline. The ISER gatherings are a venue where scientists can gather and talk about robotics based on this central tenet.

Multimodal Behavior Analysis in the Wild

Multimodal Behavior Analysis in the Wild
Author: Xavier Alameda-Pineda,Elisa Ricci,Nicu Sebe
Publsiher: Academic Press
Total Pages: 498
Release: 2018-11-13
Genre: Computers
ISBN: 9780128146026

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Multimodal Behavioral Analysis in the Wild: Advances and Challenges presents the state-of- the-art in behavioral signal processing using different data modalities, with a special focus on identifying the strengths and limitations of current technologies. The book focuses on audio and video modalities, while also emphasizing emerging modalities, such as accelerometer or proximity data. It covers tasks at different levels of complexity, from low level (speaker detection, sensorimotor links, source separation), through middle level (conversational group detection, addresser and addressee identification), and high level (personality and emotion recognition), providing insights on how to exploit inter-level and intra-level links. This is a valuable resource on the state-of-the- art and future research challenges of multi-modal behavioral analysis in the wild. It is suitable for researchers and graduate students in the fields of computer vision, audio processing, pattern recognition, machine learning and social signal processing. Gives a comprehensive collection of information on the state-of-the-art, limitations, and challenges associated with extracting behavioral cues from real-world scenarios Presents numerous applications on how different behavioral cues have been successfully extracted from different data sources Provides a wide variety of methodologies used to extract behavioral cues from multi-modal data

Transactions on Pattern Languages of Programming III

Transactions on Pattern Languages of Programming III
Author: James Noble,Ralph Johnson,Uwe Zdun,Eugene Wallingford
Publsiher: Springer
Total Pages: 195
Release: 2013-05-31
Genre: Computers
ISBN: 9783642386763

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The Transactions on Pattern Languages of Programming subline aims to publish papers on patterns and pattern languages as applied to software design, development, and use, throughout all phases of the software life cycle, from requirements and design to implementation, maintenance and evolution. The primary focus of this LNCS Transactions subline is on patterns, pattern collections, and pattern languages themselves. The journal also includes reviews, survey articles, criticisms of patterns and pattern languages, as well as other research on patterns and pattern languages. This book, the third volume in the Transactions on Pattern Languages of Programming series, presents five papers that have been through a careful peer review process involving both pattern experts and domain experts. The papers present various pattern languages and a study of applying patterns and represent some of the best work that has been carried out in design patterns and pattern languages of programming over the last few years.

Screens and Scenes

Screens and Scenes
Author: Richard Kern,Christine Develotte
Publsiher: Routledge
Total Pages: 328
Release: 2018-06-21
Genre: Language Arts & Disciplines
ISBN: 9781315447100

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This book examines the relationships between online visual interfaces and language use in educational contexts and the features that underpin them to explore the complex nature of online communication and its implications for educational practice. Adopting a case study approach featuring a global range of examples, the volume uniquely focuses on multimodal intercultural interactions, with a particular interest in videoconferencing, to look at how they project and reflect particular cultural values and tendencies concerning language use and how they elucidate the complex cultural identifications and affiliations inherent in intercultural encounters. The book employs a diverse range of theoretical and research frameworks to highlight the dynamic connections between digital technology, social life, and language use, and the ways in which they can inform language education, making this an ideal resource for students and scholars in applied linguistics, communication studies, media studies, information studies, and education.

Computer Vision ECCV 2020

Computer Vision     ECCV 2020
Author: Andrea Vedaldi,Horst Bischof,Thomas Brox,Jan-Michael Frahm
Publsiher: Springer Nature
Total Pages: 799
Release: 2020-11-11
Genre: Computers
ISBN: 9783030585655

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The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic. The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.

Vision Models for High Dynamic Range and Wide Colour Gamut Imaging

Vision Models for High Dynamic Range and Wide Colour Gamut Imaging
Author: Marcelo Bertalmío
Publsiher: Academic Press
Total Pages: 324
Release: 2019-11-06
Genre: Computers
ISBN: 9780128138953

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To enhance the overall viewing experience (for cinema, TV, games, AR/VR) the media industry is continuously striving to improve image quality. Currently the emphasis is on High Dynamic Range (HDR) and Wide Colour Gamut (WCG) technologies, which yield images with greater contrast and more vivid colours. The uptake of these technologies, however, has been hampered by the significant challenge of understanding the science behind visual perception. Vision Models for High Dynamic Range and Wide Colour Gamut Imaging provides university researchers and graduate students in computer science, computer engineering, vision science, as well as industry R&D engineers, an insight into the science and methods for HDR and WCG. It presents the underlying principles and latest practical methods in a detailed and accessible way, highlighting how the use of vision models is a key element of all state-of-the-art methods for these emerging technologies. Presents the underlying vision science principles and models that are essential to the emerging technologies of HDR and WCG Explores state-of-the-art techniques for tone and gamut mapping Discusses open challenges and future directions of HDR and WCG research

Handbook of Deep Learning Applications

Handbook of Deep Learning Applications
Author: Valentina Emilia Balas,Sanjiban Sekhar Roy,Dharmendra Sharma,Pijush Samui
Publsiher: Springer
Total Pages: 383
Release: 2019-02-25
Genre: Technology & Engineering
ISBN: 9783030114794

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This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.

Metaheuristics in Machine Learning Theory and Applications

Metaheuristics in Machine Learning  Theory and Applications
Author: Diego Oliva
Publsiher: Springer Nature
Total Pages: 765
Release: 2022
Genre: Computational intelligence
ISBN: 9783030705428

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This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities.

Proceedings of the Future Technologies Conference FTC 2021 Volume 1

Proceedings of the Future Technologies Conference  FTC  2021  Volume 1
Author: Kohei Arai
Publsiher: Springer Nature
Total Pages: 135
Release: 2022
Genre: Electronic Book
ISBN: 9783030899066

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