Hacking the Kinect
Hacking the Kinect is the technogeek’s guide to developing software and creating projects involving the groundbreaking volumetric sensor known as the Microsoft Kinect. Microsoft’s release of the Kinect in the fall of 2010 startled the technology world by providing a low-cost sensor that can detect a...
| Autor principal: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
New York :
Apress
2012.
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| Edición: | 1st ed. 2012. |
| Colección: | Technology in action
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628611006719 |
Tabla de Contenidos:
- Title Page; Copyright Page; Table of Contents; About the Authors; About the Technical Reviewer; Acknowledgments; CHAPTER 1 Introducing the Kinect; Hardware Requirements and Overview; Installing Drivers; Windows; Linux; Ubuntu; Red Hat / Fedora; Mac OS X; Testing Your Installation; Getting Help; Summary; RGB Camera; Kinect RGB Demo; Installation; Windows; Linux; Ubuntu/Debian; Red Hat/Fedora; Mac OS X; Making a Calibration Target; Calibrating with RGB Demo; Summary; CHAPTER 3 Software; Exploring the Kinect Drivers; OpenNI; Microsoft Kinect SDK; OpenKinect; Installing OpenCV; Windows; Linux
- Mac OS XInstalling the Point Cloud Library (PCL); Windows; Linux; Ubuntu; Debian; Mac OS X; Summary; CHAPTER 4 Computer Vision; Anatomy of an Image; Image Processing Basics; Simplifying Data; Contriving Your Situation; Brightness Thresholding; Brightest Pixel Tracking; Comparing Images; Thresholding with a Tolerance; Background Subtraction; Frame Differencing; Combining Frame Differencing with Background Subtraction; Summary; CHAPTER 5 Gesture Recognition; What Is a Gesture?; Multitouch Detection; Acquiring the Camera Image, Storing the Background, andSubtracting
- Applying the Threshold FilterIdentifying Connected Components; Assigning and Tracking Component IDs; Calculating Gestures; Detecting Motion; Rotation; Scale; Creating a Minority Report-Style Interface; Considering Shape Gestures; Summary; CHAPTER 6 Voxelization; What Is a Voxel?; Why Voxelize Data?; Voxelizing Data; Manipulating Voxels; Clustering Voxels; Tracking People and Fitting a Rectangular Prism; Summary; CHAPTER 7 Point Clouds, Part 1; Representing Data in 3-D; Creating a Point Cloud with PCL; Moving From Depth Map to Point Cloud; Coloring a Point Cloud
- From Depth to Color Reference FrameProjecting onto the Color Image Plane; Visualizing a Point Cloud; Visualizing with PCL; Visualizing with OpenGL; Summary; CHAPTER 8 Point Clouds, Part 2; Registration; 2-D Registration; 3-D Registration; Robustness to Outliers; Simultaneous Localization and Mapping (SLAM); SLAM Using a Conventional Camera; Advantages of Using the Kinect for SLAM; A SLAM Algorithm Using the Kinect; Real-Time Considerations; Surface Reconstruction; Normal Estimation; Triangulation of Points; Summary; CHAPTER 9 Object Modeling and Detection
- Acquiring an Object Model Using a Single Kinect ImageTabletop Object Detector; Extracting the Table Plane; Keeping Only Points Lying on the Table; Extracting Individual Object Clusters; Fitting a Parametric Model to a Point Cloud; Building a 3-DModel by Extrusion; Construction of a Voxelized Representation; Filling Unseen Voxels; Building a Surface Point Cloud; Building a Mesh; Acquiring a 3-D Object Model Using Multiple Views; Overview of a Marker-Based Scanner; Building a Support with Markers; Estimating the 3-DCenter of the Markers in the Camera Space; Kinect Pose Estimation from Markers
- Cleaning and Cropping the Partial Views
