- Full Description
The potential of consumer depth cameras extends well beyond entertainment and gaming, to real-world commercial applications. This authoritative text reviews the scope and impact of this rapidly growing field, describing the most promising Kinect-based research activities, discussing significant current challenges, and showcasing exciting applications. Features: presents contributions from an international selection of preeminent authorities in their fields, from both academic and corporate research; addresses the classic problem of multi-view geometry of how to correlate images from different viewpoints to simultaneously estimate camera poses and world points; examines human pose estimation using video-rate depth images for gaming, motion capture, 3D human body scans, and hand pose recognition for sign language parsing; provides a review of approaches to various recognition problems, including category and instance learning of objects, and human activity recognition; with a Foreword by Dr. Jamie Shotton.
- Table of Contents
Table of Contents
- Part I: 3D Registration and Reconstruction.
- 3D with Kinect.
- Time RGB
- D Mapping and 3
- D Modeling on the GPU using the Random Ball Cover.
- A Brute Force Approach to Depth Camera Odometry.
- Part II: Human Body Analysis.
- Key Developments in Human Pose Estimation for Kinect.
- A Data
- Driven Approach for Real
- Time Full Body Pose Reconstruction from a Depth Camera.
- Home 3D Body Scans from a Single Kinect.
- Time Hand Pose Estimation using Depth Sensors.
- Part III: RGB
- D Datasets.
- A Category
- Level 3D Object Dataset: Putting the Kinect to Work.
- D Object Recognition: Features, Algorithms, and a Large Scale Benchmark.
- HuDaAct: A Color
- Depth Video Database for Human Daily Activity Recognition.
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