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RGB-D Image Analysis and Processing

Overview of attention for book
Cover of 'RGB-D Image Analysis and Processing'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Commodity RGB-D Sensors: Data Acquisition
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    Chapter 2 Dealing with Missing Depth: Recent Advances in Depth Image Completion and Estimation
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    Chapter 3 Depth Super-Resolution with Color Guidance: A Review
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    Chapter 4 RGB-D Sensors Data Quality Assessment and Improvement for Advanced Applications
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    Chapter 5 3D Reconstruction from RGB-D Data
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    Chapter 6 RGB-D Odometry and SLAM
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    Chapter 7 Enhancing 3D Capture with Multiple Depth Camera Systems: A State-of-the-Art Report
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    Chapter 8 RGB-D Image-Based Object Detection: From Traditional Methods to Deep Learning Techniques
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    Chapter 9 RGB-D Salient Object Detection: A Review
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    Chapter 10 Foreground Detection and Segmentation in RGB-D Images
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    Chapter 11 Instance- and Category-Level 6D Object Pose Estimation
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    Chapter 12 Geometric and Semantic Modeling from RGB-D Data
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    Chapter 13 Semantic RGB-D Perception for Cognitive Service Robots
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    Chapter 14 RGB-D Sensors and Signal Processing for Fall Detection
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    Chapter 15 RGB-D Interactive Systems on Serious Games for Motor Rehabilitation Therapy and Therapeutic Measurements
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    Chapter 16 Real-Time Hand Pose Estimation Using Depth Camera
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    Chapter 17 RGB-D Object Classification for Autonomous Driving Perception
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    Chapter 18 People Counting in Crowded Environment and Re-identification
Attention for Chapter 8: RGB-D Image-Based Object Detection: From Traditional Methods to Deep Learning Techniques
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Citations

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Readers on

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83 Mendeley
Summary Dimensions citations
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Chapter title
RGB-D Image-Based Object Detection: From Traditional Methods to Deep Learning Techniques
Chapter number 8
Book title
RGB-D Image Analysis and Processing
Published by
Springer, Cham, January 2019
DOI 10.1007/978-3-030-28603-3_8
Book ISBNs
978-3-03-028602-6, 978-3-03-028603-3
Authors

Isaac Ronald Ward, Hamid Laga, Mohammed Bennamoun, Ward, Isaac Ronald, Laga, Hamid, Bennamoun, Mohammed

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 83 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 23%
Student > Master 16 19%
Researcher 8 10%
Student > Bachelor 5 6%
Other 4 5%
Other 6 7%
Unknown 25 30%
Readers by discipline Count As %
Computer Science 30 36%
Engineering 23 28%
Unspecified 2 2%
Arts and Humanities 1 1%
Mathematics 1 1%
Other 1 1%
Unknown 25 30%

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