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Author: Huchuan Lu Publisher: Springer ISBN: 9811304696 Category : Computers Languages : en Pages : 134
Book Description
This book presents the state of the art in online visual tracking, including the motivations, practical algorithms, and experimental evaluations. Visual tracking remains a highly active area of research in Computer Vision and the performance under complex scenarios has substantially improved, driven by the high demand in connection with real-world applications and the recent advances in machine learning. A large variety of new algorithms have been proposed in the literature over the last two decades, with mixed success. Chapters 1 to 6 introduce readers to tracking methods based on online learning algorithms, including sparse representation, dictionary learning, hashing codes, local model, and model fusion. In Chapter 7, visual tracking is formulated as a foreground/background segmentation problem, and tracking methods based on superpixels and end-to-end deep networks are presented. In turn, Chapters 8 and 9 introduce the cutting-edge tracking methods based on correlation filter and deep learning. Chapter 10 summarizes the book and points out potential future research directions for visual tracking. The book is self-contained and suited for all researchers, professionals and postgraduate students working in the fields of computer vision, pattern recognition, and machine learning. It will help these readers grasp the insights provided by cutting-edge research, and benefit from the practical techniques available for designing effective visual tracking algorithms. Further, the source codes or results of most algorithms in the book are provided at an accompanying website.
Author: Huchuan Lu Publisher: Springer ISBN: 9811304696 Category : Computers Languages : en Pages : 134
Book Description
This book presents the state of the art in online visual tracking, including the motivations, practical algorithms, and experimental evaluations. Visual tracking remains a highly active area of research in Computer Vision and the performance under complex scenarios has substantially improved, driven by the high demand in connection with real-world applications and the recent advances in machine learning. A large variety of new algorithms have been proposed in the literature over the last two decades, with mixed success. Chapters 1 to 6 introduce readers to tracking methods based on online learning algorithms, including sparse representation, dictionary learning, hashing codes, local model, and model fusion. In Chapter 7, visual tracking is formulated as a foreground/background segmentation problem, and tracking methods based on superpixels and end-to-end deep networks are presented. In turn, Chapters 8 and 9 introduce the cutting-edge tracking methods based on correlation filter and deep learning. Chapter 10 summarizes the book and points out potential future research directions for visual tracking. The book is self-contained and suited for all researchers, professionals and postgraduate students working in the fields of computer vision, pattern recognition, and machine learning. It will help these readers grasp the insights provided by cutting-edge research, and benefit from the practical techniques available for designing effective visual tracking algorithms. Further, the source codes or results of most algorithms in the book are provided at an accompanying website.
Author: Huchuan Lu Publisher: Springer ISBN: 9789811304682 Category : Computers Languages : en Pages : 128
Book Description
This book presents the state of the art in online visual tracking, including the motivations, practical algorithms, and experimental evaluations. Visual tracking remains a highly active area of research in Computer Vision and the performance under complex scenarios has substantially improved, driven by the high demand in connection with real-world applications and the recent advances in machine learning. A large variety of new algorithms have been proposed in the literature over the last two decades, with mixed success. Chapters 1 to 6 introduce readers to tracking methods based on online learning algorithms, including sparse representation, dictionary learning, hashing codes, local model, and model fusion. In Chapter 7, visual tracking is formulated as a foreground/background segmentation problem, and tracking methods based on superpixels and end-to-end deep networks are presented. In turn, Chapters 8 and 9 introduce the cutting-edge tracking methods based on correlation filter and deep learning. Chapter 10 summarizes the book and points out potential future research directions for visual tracking. The book is self-contained and suited for all researchers, professionals and postgraduate students working in the fields of computer vision, pattern recognition, and machine learning. It will help these readers grasp the insights provided by cutting-edge research, and benefit from the practical techniques available for designing effective visual tracking algorithms. Further, the source codes or results of most algorithms in the book are provided at an accompanying website.
Author: Keli Hu Publisher: Infinite Study ISBN: Category : Mathematics Languages : en Pages : 24
Book Description
An online neutrosophic similarity-based objectness tracking with a weighted multiple instance learning algorithm (NeutWMIL) is proposed. Each training sample is extracted surrounding the object location, and the distribution of these samples is symmetric. To provide a more robust weight for each sample in the positive bag, the asymmetry of the importance of the samples is considered. The neutrosophic similarity-based objectness estimation with object properties (super straddling) is applied.
Author: Jakob Nielsen Publisher: New Riders ISBN: 0321714075 Category : Computers Languages : en Pages : 457
Book Description
Eyetracking Web Usability is based on one of the largest studies of eyetracking usability in existence. Best-selling author Jakob Nielsen and coauthor Kara Pernice used rigorous usability methodology and eyetracking technology to analyze 1.5 million instances where users look at Web sites to understand how the human eyes interact with design. Their findings will help designers, software developers, writers, editors, product managers, and advertisers understand what people see or don’t see, when they look, and why. With their comprehensive three-year study, the authors confirmed many known Web design conventions and the book provides additional insights on those standards. They also discovered important new user behaviors that are revealed here for the first time. Using compelling eye gaze plots and heat maps, Nielsen and Pernice guide the reader through hundreds of examples of eye movements, demonstrating why some designs work and others don’t. They also provide valuable advice for page layout, navigation menus, site elements, image selection, and advertising. This book is essential reading for anyone who is serious about doing business on the Web.
Author: Andrew Duchowski Publisher: Springer Science & Business Media ISBN: 1846286093 Category : Computers Languages : en Pages : 336
Book Description
Despite the availability of cheap, fast, accurate and usable eye trackers, there is little information available on how to develop, implement and use these systems. This 2nd edition of the successful guide contains significant additional material on the topic and aims to fill that gap in the market by providing an accessible and comprehensive introduction. Additional key features of the 2nd edition include: Technical description of new (state-of-the-art) eye tracking technology; a complete whole new section describing experimental methodology including experimental design, empirical guidelines, and five case studies; and survey material regarding recent research publications.
Author: Bridgette Sharp Publisher: Createspace Independent Publishing Platform ISBN: 9781985229228 Category : Languages : en Pages : 62
Book Description
VISUAL TRACKING, the required skill for successful READING, WRITING and most other ACADEMICS! VISUAL TRACKING, the first skill mastered in SPEED READING! Visual Tracking Skills improve: 1.Reading Speed 2.Reading Accuracy 3.Attention to Detail 4.Reading Comprehension 5.Letter and Number Reversals 6.Sequencing 7.Visual Processing 8.Brain Processing 9.Brain Timing Using the techniques in this book, your student can improve visual processing skills, sequencing skills, improve visual tracking and lessen the occurrence of reversals. This form of cognitive therapy can be used by therapists, teachers, tutors and parents to teach and reinforce important skills necessary for successful reading and writing
Author: Ashish Kumar Publisher: CRC Press ISBN: 1000990982 Category : Technology & Engineering Languages : en Pages : 216
Book Description
This book covers the description of both conventional methods and advanced methods. In conventional methods, visual tracking techniques such as stochastic, deterministic, generative, and discriminative are discussed. The conventional techniques are further explored for multi-stage and collaborative frameworks. In advanced methods, various categories of deep learning-based trackers and correlation filter-based trackers are analyzed. The book also: Discusses potential performance metrics used for comparing the efficiency and effectiveness of various visual tracking methods Elaborates on the salient features of deep learning trackers along with traditional trackers, wherein the handcrafted features are fused to reduce computational complexity Illustrates various categories of correlation filter-based trackers suitable for superior and efficient performance under tedious tracking scenarios Explores the future research directions for visual tracking by analyzing the real-time applications The book comprehensively discusses various deep learning-based tracking architectures along with conventional tracking methods. It covers in-depth analysis of various feature extraction techniques, evaluation metrics and benchmark available for performance evaluation of tracking frameworks. The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.
Author: Jinfeng Yang Publisher: Springer ISBN: 9811073058 Category : Computers Languages : en Pages : 740
Book Description
This three volume set, CCIS 771, 772, 773, constitutes the refereed proceedings of the CCF Chinese Conference on Computer Vision, CCCV 2017, held in Tianjin, China, in October 2017. The total of 174 revised full papers presented in three volumes were carefully reviewed and selected from 465 submissions. The papers are organized in the following topical sections: biological vision inspired visual method; biomedical image analysis; computer vision applications; deep neural network; face and posture analysis; image and video retrieval; image color and texture; image composition; image quality assessment and analysis; image restoration; image segmentation and classification; image-based modeling; object detection and classification; object identification; photography and video; robot vision; shape representation and matching; statistical methods and learning; video analysis and event recognition; visual salient detection.
Author: Weiwei Xing Publisher: Springer Nature ISBN: 9811662428 Category : Computers Languages : en Pages : 202
Book Description
The book focuses on visual object tracking systems and approaches based on correlation filter and deep learning. Both foundations and implementations have been addressed. The algorithm, system design and performance evaluation have been explored for three kinds of tracking methods including correlation filter based methods, correlation filter with deep feature based methods, and deep learning based methods. Firstly, context aware and multi-scale strategy are presented in correlation filter based trackers; then, long-short term correlation filter, context aware correlation filter and auxiliary relocation in SiamFC framework are proposed for combining correlation filter and deep learning in visual object tracking; finally, improvements in deep learning based trackers including Siamese network, GAN and reinforcement learning are designed. The goal of this book is to bring, in a timely fashion, the latest advances and developments in visual object tracking, especially correlation filter and deep learning based methods, which is particularly suited for readers who are interested in the research and technology innovation in visual object tracking and related fields.
Author: Huchuan Lu
Author: Huchuan Lu
Author: Huchuan Lu
Author: Keli Hu
Author: Jakob Nielsen
Author: Andrew Duchowski
Author: Bridgette Sharp
Author: Ashish Kumar
Author: Ning Xu
Author: Jinfeng Yang
Author: Weiwei Xing