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Advanced Topics in Computer Vision

Overview of attention for book
Cover of 'Advanced Topics in Computer Vision'

Table of Contents

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    Book Overview
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    Chapter 1 Visual Features—From Early Concepts to Modern Computer Vision
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    Chapter 2 Where Next in Object Recognition and how much Supervision Do We Need?
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    Chapter 3 Recognizing Human Actions by Using Effective Codebooks and Tracking
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    Chapter 4 Evaluating and Extending Trajectory Features for Activity Recognition
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    Chapter 5 Co-recognition of Images and Videos: Unsupervised Matching of Identical Object Patterns and Its Applications
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    Chapter 6 Stereo Matching—State-of-the-Art and Research Challenges
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    Chapter 7 Visual Localization for Micro Aerial Vehicles in Urban Outdoor Environments
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    Chapter 8 Moment Constraints in Convex Optimization for Segmentation and Tracking
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    Chapter 9 Large Scale Metric Learning for Distance-Based Image Classification on Open Ended Data Sets
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    Chapter 10 Top–Down Bayesian Inference of Indoor Scenes
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    Chapter 11 Efficient Loopy Belief Propagation Using the Four Color Theorem
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    Chapter 12 Boosting k -Nearest Neighbors Classification
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    Chapter 13 Learning Object Detectors in Stationary Environments
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    Chapter 14 Video Temporal Super-resolution Based on Self-similarity
Attention for Chapter 13: Learning Object Detectors in Stationary Environments
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Citations

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Chapter title
Learning Object Detectors in Stationary Environments
Chapter number 13
Book title
Advanced Topics in Computer Vision
Published by
Springer, London, January 2013
DOI 10.1007/978-1-4471-5520-1_13
Book ISBNs
978-1-4471-5519-5, 978-1-4471-5520-1
Authors

Peter M. Roth, Sabine Sternig, Horst Bischof, Roth, Peter M., Sternig, Sabine, Bischof, Horst

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 75%
Other 1 25%
Readers by discipline Count As %
Engineering 2 50%
Agricultural and Biological Sciences 1 25%
Computer Science 1 25%

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