Visual Object Tracking from Correlation Filter to Deep Learning

Language: English

Published by Springer Nature Singapore Nov 2021, 2021

981166241X / 9789811662416

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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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This item is printed on demand - it takes 3-4 days longer - Neuware -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. 208 pp. Englisch.…

Seller Inventory # 9789811662416

Title
Visual Object Tracking from Correlation Filter to Deep Learning
Author
Weiwei Xing
Publisher
Springer Nature Singapore Nov 2021
Publication year
2021
Condition
Neu
Binding
Buch
Language
English
ISBN 10
981166241X
ISBN 13
9789811662416
Item weight
521 grams
Dimensions
241x160x17 mm

BuchWeltWeit Ludwig Meier e.K.

Bergisch Gladbach, Germany

5-star seller

AbeBooks seller since January 11, 2012

Shipping rates from Germany to U.S.A.

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BuchWeltWeit Ludwig Meier e.K.

Germany