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OpenCV with Python blueprints : design and develop advanced computer vision projects using OpenCV with Python /
Design and develop advanced computer vision projects using OpenCV with Python About This Book Program advanced computer vision applications in Python using different features of the OpenCV library Practical end-to-end project covering an important computer vision problem All projects in the book inc...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham, UK :
Packt Publishing,
2015.
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| Colección: | Community experience distilled.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Cover ; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Fun with Filters; Planning the app; Creating a black-and-white pencil sketch; Implementing dodging and burning in OpenCV; Pencil sketch transformation; Generating a warming/cooling filter; Color manipulation via curve shifting; Implementing a curve filter by using lookup tables; Designing the warming/cooling effect; Cartoonizing an image; Using a bilateral filter for edge-aware smoothing; Detecting and emphasizing prominent edges.
- Combining colors and outlines to produce a cartoonPutting it all together; Running the app; The GUI base class; The GUI constructor; Handling video streams; A basic GUI layout; A custom filter layout; Summary; Chapter 2: Hand Gesture Recognition Using a Kinect Depth Sensor; Planning the app; Setting up the app; Accessing the Kinect 3D sensor; Running the app; The Kinect GUI; Tracking hand gestures in real time; Hand region segmentation; Finding the most prominent depth of the image center region; Applying morphological closing to smoothen the segmentation mask.
- Finding connected components in a segmentation maskHand shape analysis; Determining the contour of the segmented hand region; Finding the convex hull of a contour area; Finding the convexity defects of a convex hull; Hand gesture recognition; Distinguishing between different causes of convexity defects; Classifying hand gestures based on the number of extended fingers; Summary; Chapter 3: Finding Objects via Feature Matching and Perspective Transforms; Tasks performed by the app; Planning the app; Setting up the app; Running the app; The FeatureMatching GUI; The process flow.
- Feature extractionFeature detection; Detecting features in an image with SURF; Feature matching; Matching features across images with FLANN; The ratio test for outlier removal; Visualizing feature matches; Homography estimation; Warping the image; Feature tracking; Early outlier detection and rejection; Seeing the algorithm in action; Summary; Chapter 4: 3D Scene Reconstruction Using Structure from Motion; Planning the app; Camera calibration; The pinhole camera model; Estimating the intrinsic camera parameters; The camera calibration GUI; Initializing the algorithm.
- Collecting image and object pointsFinding the camera matrix; Setting up the app; The main function routine; The SceneReconstruction3D class; Estimating the camera motion from a pair of images; Point matching using rich feature descriptors; Point matching using optic flow; Finding the camera matrices; Image rectification; Reconstructing the scene; 3D point cloud visualization; Summary; Chapter 5: Tracking Visually Salient Objects; Planning the app; Setting up the app; The main function routine; The Saliency class; The MultiObjectTracker class; Visual saliency; Fourier analysis.