Online Public Access Catalogue (OPAC)
Library,Documentation and Information Science Division

“A research journal serves that narrow

borderland which separates the known from the unknown”

-P.C.Mahalanobis


Image from Google Jackets

Computer vision and machine learning with RGB-D sensors / [edited by] Ling Shao...[et al.].

Contributor(s): Material type: TextTextSeries: Advances in computer vision and pattern recognitionPublication details: Switzerland : Springer, 2014.Description: x, 316 p. : illustrations (chiefly color) ; 24 cmISBN:
  • 9783319086507
Subject(s): DDC classification:
  • 006.37 23 Sh528
Contents:
Part I: Surveys -- 1. 3D Depth Cameras in Vision: Benefits and Limitations of the Hardware -- 2. A State-of-the-Art Report on Multiple RGB-D Sensor Research and on Publicly Available RGB-D Datasets -- Part II: Reconstruction, Mapping and Synthesis -- 3. Calibration Between Depth and Color Sensors for Commodity Depth Cameras -- 4. Depth Map Denoising via CDT-Based Joint Bilateral Filter -- 5. Human Performance Capture Using Multiple Handheld Kinects -- 6. Human Centered 3D Home Applications via Low-Cost RGBD Cameras -- 7. Matching of 3D Objects Based on 3D Curves -- 8. Using Sparse Optical Flow for Two-Phase Gas Flow Capturing with Multiple Kinects -- Part III: Detection, Segmentation and Tracking -- 9. RGB-D Sensor-Based Computer Vision Assistive Technology for Visually Impaired Persons -- 10. RGB-D Human Identification and Tracking in a Smart Environment -- Part IV: Learning-Based Recognition -- 11. Feature Descriptors for Depth-Based Hand Gesture Recognition -- 12. Hand Parsing and Gesture Recognition with a Commodity Depth Camera -- 13. Learning Fast Hand Pose Recognition -- 14. Real time Hand-Gesture Recognition Using RGB-D Sensor-- Index.
Summary: This book presents an interdisciplinary selection of cutting-edge research on RGB-D based computer vision. Features: discusses the calibration of color and depth cameras, the reduction of noise on depth maps and methods for capturing human performance in 3D; reviews a selection of applications which use RGB-D information to reconstruct human figures, evaluate energy consumption and obtain accurate action classification; presents an approach for 3D object retrieval and for the reconstruction of gas flow from multiple Kinect cameras; describes an RGB-D computer vision system designed to assist the visually impaired and another for smart-environment sensing to assist elderly and disabled people; examines the effective features that characterize static hand poses and introduces a unified framework to enforce both temporal and spatial constraints for hand parsing; proposes a new classifier architecture for real-time hand pose recognition and a novel hand segmentation and gesture recognition system.
Tags from this library: No tags from this library for this title. Log in to add tags.
Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 006.37 Sh528 (Browse shelf(Opens below)) Available 136281
Total holds: 0

Includes index.

Part I: Surveys --
1. 3D Depth Cameras in Vision: Benefits and Limitations of the Hardware --
2. A State-of-the-Art Report on Multiple RGB-D Sensor Research and on Publicly Available RGB-D Datasets --

Part II: Reconstruction, Mapping and Synthesis --
3. Calibration Between Depth and Color Sensors for Commodity Depth Cameras --
4. Depth Map Denoising via CDT-Based Joint Bilateral Filter --
5. Human Performance Capture Using Multiple Handheld Kinects --
6. Human Centered 3D Home Applications via Low-Cost RGBD Cameras --
7. Matching of 3D Objects Based on 3D Curves --
8. Using Sparse Optical Flow for Two-Phase Gas Flow Capturing with Multiple Kinects --

Part III: Detection, Segmentation and Tracking --
9. RGB-D Sensor-Based Computer Vision Assistive Technology for Visually Impaired Persons --
10. RGB-D Human Identification and Tracking in a Smart Environment --

Part IV: Learning-Based Recognition --
11. Feature Descriptors for Depth-Based Hand Gesture Recognition --
12. Hand Parsing and Gesture Recognition with a Commodity Depth Camera --
13. Learning Fast Hand Pose Recognition --
14. Real time Hand-Gesture Recognition Using RGB-D Sensor--
Index.

This book presents an interdisciplinary selection of cutting-edge research on RGB-D based computer vision. Features: discusses the calibration of color and depth cameras, the reduction of noise on depth maps and methods for capturing human performance in 3D; reviews a selection of applications which use RGB-D information to reconstruct human figures, evaluate energy consumption and obtain accurate action classification; presents an approach for 3D object retrieval and for the reconstruction of gas flow from multiple Kinect cameras; describes an RGB-D computer vision system designed to assist the visually impaired and another for smart-environment sensing to assist elderly and disabled people; examines the effective features that characterize static hand poses and introduces a unified framework to enforce both temporal and spatial constraints for hand parsing; proposes a new classifier architecture for real-time hand pose recognition and a novel hand segmentation and gesture recognition system.

There are no comments on this title.

to post a comment.
Library, Documentation and Information Science Division, Indian Statistical Institute, 203 B T Road, Kolkata 700108, INDIA
Phone no. 91-33-2575 2100, Fax no. 91-33-2578 1412, ksatpathy@isical.ac.in