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Author: Avik Hati Publisher: Springer Nature ISBN: 9811985707 Category : Technology & Engineering Languages : en Pages : 231
Book Description
This book presents and analyzes methods to perform image co-segmentation. In this book, the authors describe efficient solutions to this problem ensuring robustness and accuracy, and provide theoretical analysis for the same. Six different methods for image co-segmentation are presented. These methods use concepts from statistical mode detection, subgraph matching, latent class graph, region growing, graph CNN, conditional encoder–decoder network, meta-learning, conditional variational encoder–decoder, and attention mechanisms. The authors have included several block diagrams and illustrative examples for the ease of readers. This book is a highly useful resource to researchers and academicians not only in the specific area of image co-segmentation but also in related areas of image processing, graph neural networks, statistical learning, and few-shot learning.
Author: Avik Hati Publisher: Springer Nature ISBN: 9811985707 Category : Technology & Engineering Languages : en Pages : 231
Book Description
This book presents and analyzes methods to perform image co-segmentation. In this book, the authors describe efficient solutions to this problem ensuring robustness and accuracy, and provide theoretical analysis for the same. Six different methods for image co-segmentation are presented. These methods use concepts from statistical mode detection, subgraph matching, latent class graph, region growing, graph CNN, conditional encoder–decoder network, meta-learning, conditional variational encoder–decoder, and attention mechanisms. The authors have included several block diagrams and illustrative examples for the ease of readers. This book is a highly useful resource to researchers and academicians not only in the specific area of image co-segmentation but also in related areas of image processing, graph neural networks, statistical learning, and few-shot learning.
Author: Dhruv Batra Publisher: Springer Science & Business Media ISBN: 1461419158 Category : Computers Languages : en Pages : 56
Book Description
The authors survey a recent technique in computer vision called Interactive Co-segmentation, which is the task of simultaneously extracting common foreground objects from multiple related images. They survey several of the algorithms, present underlying common ideas, and give an overview of applications of object co-segmentation.
Author: Ismail Ben Ayed Publisher: Academic Press ISBN: 0128092297 Category : Technology & Engineering Languages : en Pages : 184
Book Description
High-Order Models in Semantic Image Segmentation reviews recent developments in optimization-based methods for image segmentation, presenting several geometric and mathematical models that underlie a broad class of recent segmentation techniques. Focusing on impactful algorithms in the computer vision community in the last 10 years, the book includes sections on graph-theoretic and continuous relaxation techniques, which can compute globally optimal solutions for many problems. The book provides a practical and accessible introduction to these state-of -the-art segmentation techniques that is ideal for academics, industry researchers, and graduate students in computer vision, machine learning and medical imaging. Gives an intuitive and conceptual understanding of this mathematically involved subject by using a large number of graphical illustrations Provides the right amount of knowledge to apply sophisticated techniques for a wide range of new applications Contains numerous tables that compare different algorithms, facilitating the appropriate choice of algorithm for the intended application Presents an array of practical applications in computer vision and medical imaging Includes code for many of the algorithms that is available on the book’s companion website
Author: Paul L. Rosin Publisher: Springer Nature ISBN: 3030286037 Category : Computers Languages : en Pages : 524
Book Description
This book focuses on the fundamentals and recent advances in RGB-D imaging as well as covering a range of RGB-D applications. The topics covered include: data acquisition, data quality assessment, filling holes, 3D reconstruction, SLAM, multiple depth camera systems, segmentation, object detection, salience detection, pose estimation, geometric modelling, fall detection, autonomous driving, motor rehabilitation therapy, people counting and cognitive service robots. The availability of cheap RGB-D sensors has led to an explosion over the last five years in the capture and application of colour plus depth data. The addition of depth data to regular RGB images vastly increases the range of applications, and has resulted in a demand for robust and real-time processing of RGB-D data. There remain many technical challenges, and RGB-D image processing is an ongoing research area. This book covers the full state of the art, and consists of a series of chapters by internationally renowned experts in the field. Each chapter is written so as to provide a detailed overview of that topic. RGB-D Image Analysis and Processing will enable both students and professional developers alike to quickly get up to speed with contemporary techniques, and apply RGB-D imaging in their own projects.
Author: David Fleet Publisher: Springer ISBN: 9783319105833 Category : Computers Languages : en Pages : 632
Book Description
The seven-volume set comprising LNCS volumes 8689-8695 constitutes the refereed proceedings of the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014. The 363 revised papers presented were carefully reviewed and selected from 1444 submissions. The papers are organized in topical sections on tracking and activity recognition; recognition; learning and inference; structure from motion and feature matching; computational photography and low-level vision; vision; segmentation and saliency; context and 3D scenes; motion and 3D scene analysis; and poster sessions.
Author: Chuan Wang Publisher: ISBN: 9781361035900 Category : Languages : en Pages :
Book Description
This dissertation, "Video Object Co-segmentation and Video Vectorization" by Chuan, Wang, 王氚, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Video, as a rapidly growing multimedia data, has been increasingly affecting our life in expression communication and interactions with the outer world. Compared to traditional image or text, it has better ability to convey information due to its time-sequential nature which, however, makes it a challenging task to extract information from it or process it. To keep up with its rapid extension, the research community has endeavored to develop accompanying tools that assist users analyzing and processing videos. This thesis demonstrates two systems for video analysis and process, video object co-segmentation and video vectorization. In the system of video object co-segmentation, we address an issue of co-segmenting the common foreground object from a group of video sequences based on that multiple videos may share a common foreground object, such as a family member in home videos or a leading role in various clips of a movie or TV series. We propose a novel co-segmentation algorithm for video by taking full advantage of its appearance and motion features. Our algorithm is well-designed so that it can be differentiated from the algorithms for other forms of data, e.g. image or geometric shapes. We compare our method with the existing related works and our approach outperforms state-of-the-art methods. In the system of video vectorization, we study a vectorization method for videos. Vector-based graphical contents are being increasingly used in smartphones and computers, and becoming the main form of media on the Internet, demonstrated by the popularity of vectorized image editing tools such as Adobe Illustrator or CorelDraw. We realize that it would not work if simply applying existing image vectorization techniques to individual frames, because of the lack of consideration of temporal coherence between video frames that would cause unacceptable flickering. Consequently, we propose a method that treats the video as a spatial-temporal volume and uses 3D tetrahedral meshes for the vector-based representation. We present novel techniques for simplification and subdivision of a tetrahedral mesh to achieve high simplification ratio while preserving features and ensuring color fidelity. The proposed mesh simplification algorithm can be further applied to fast mesh generation for large-scale volumetric data with multiple labeled regions such as medical data. We also demonstrate the superiority of our approach by comparison with related works. DOI: 10.5353/th_b5570779 Subjects: Digital video
Author: Essaïd Sabir Publisher: Springer ISBN: 9812879900 Category : Technology & Engineering Languages : en Pages : 563
Book Description
This volume publishes new trends and findings in hot topics related to ubiquitous computing/networking. It is the outcome of UNet - ainternational scientific event that took place on September 08-10, 2015, in the fascinating city of Casablanca, Morocco. UNet’15 is technically sponsored by IEEE Morocco Section and IEEE COMSOC Morocco Chapter.
Author: David Fleet Publisher: Springer ISBN: 3319105841 Category : Computers Languages : en Pages : 656
Book Description
The seven-volume set comprising LNCS volumes 8689-8695 constitutes the refereed proceedings of the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014. The 363 revised papers presented were carefully reviewed and selected from 1444 submissions. The papers are organized in topical sections on tracking and activity recognition; recognition; learning and inference; structure from motion and feature matching; computational photography and low-level vision; vision; segmentation and saliency; context and 3D scenes; motion and 3D scene analysis; and poster sessions.
Author: Avik Hati
Author: Avik Hati
Author: Dhruv Batra
Author: 張芸菱
Author: Huiguang Yang
Author: Ismail Ben Ayed
Author: Paul L. Rosin
Author: David Fleet
Author: Chuan Wang
Author: Essaïd Sabir
Author: David Fleet