Online Visual Tracking
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
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Online Visual Tracking
Online Visual Tracking
Huchuan Lu Dong Wang •
Online Visual Tracking
123
Huchuan Lu Dalian University of Technology Dalian, China
Dong Wang Dalian University of Technology Dalian, China
ISBN 978-981-13-0468-2 ISBN 978-981-13-0469-9 https://doi.org/10.1007/978-981-13-0469-9
(eBook)
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Preface
This book introduces some representative trackers through practical algorithm analysis and experimental evaluations. This book is intended for professionals and researchers who are interested in visual tracking, also students can take it as a reference book. Readers will get comprehensive knowledge of tracking and can learn state-of-the-art methods through this content. In general, the book is organized as follows: Chapter 1 provides a brief introduction of visual tracking. First, we introduce basic components of tracking including representation scheme, search mechanism, and model update. Then, challenges in visual tracking are displayed. Finally, we show the datasets and evaluation metrics to evaluate trackers in the following chapters. In Chaps. 2–7, tracking methods based on sparse representation, local model, model fusion, foreground-background segmentation, correlation filters, and advanced deep learning techniques are introduced to understand tracking in a comprehensive view. In each chapter, we first give a brief introduction of the topic and the existing methods. Then, a few representative trackers and their experimental results are discussed in detail. Finally, each chapter ends with a summary. The last chapter summarizes the book and points out some
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