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Video Object Tracking [electronic resource] : Tasks, Datasets, and Methods / by Ning Xu, Weiyao Lin, Xiankai Lu, Yunchao Wei.

By: Contributor(s): Material type: TextSeries: Synthesis Lectures on Computer VisionPublisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edition: 1st ed. 2024Description: VIII, 123 p. 50 illus., 49 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031446603
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleLOC classification:
  • TA1634
Online resources:
Contents:
Chapter 1 Introduction -- Chapter 2 Tracking -- Chapter 3 HiEve Challenge on VOT.
In: Springer Nature eBookSummary: This book provides a thorough overview of recent progress in video object tracking, allowing researchers and industrial practitioners to gain a better understanding of the most important problems and developed technologies in the area. Video tracking is a key research area in computer vision and aims to track unique objects in a given video, which are useful for various applications such as video conference, video editing, surveillance, and autonomous driving. This book begins with an introduction to the task of video object tracking, including the most common problem settings. Given the revolution of deep learning in computer vision problems, numerous new tasks, datasets, and methods have been recently proposed in the domain of video tracking. The book includes these recent results as well as benchmarks in large-scale human-centric video analysis in complex events. .
Item type: List(s) this item appears in: Titluri cărți electronice Springer Nature 2025 (10631 titluri)
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Chapter 1 Introduction -- Chapter 2 Tracking -- Chapter 3 HiEve Challenge on VOT.

This book provides a thorough overview of recent progress in video object tracking, allowing researchers and industrial practitioners to gain a better understanding of the most important problems and developed technologies in the area. Video tracking is a key research area in computer vision and aims to track unique objects in a given video, which are useful for various applications such as video conference, video editing, surveillance, and autonomous driving. This book begins with an introduction to the task of video object tracking, including the most common problem settings. Given the revolution of deep learning in computer vision problems, numerous new tasks, datasets, and methods have been recently proposed in the domain of video tracking. The book includes these recent results as well as benchmarks in large-scale human-centric video analysis in complex events. .

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