- OpenCV 3 Blueprints
- Table of Contents
- OpenCV 3 Blueprints
- Credits
- About the Authors
- About the Reviewers
- www.PacktPub.com
- Preface
- 1. Getting the Most out of Your Camera System
- 2. Photographing Nature and Wildlife with an Automated Camera
- 3. Recognizing Facial Expressions with Machine Learning
- Introducing facial expression recognition
- Finding the face region in the image
- Feature extraction
- Classification
- Evaluation
- System overview
- Further reading
- Summary
- 4. Panoramic Image Stitching Application Using Android Studio and NDK
- Introducing the concept of panorama
- The Android section – an application user interface
- Integrating OpenCV into the Android Studio
- Application showcase
- Further improvement
- Summary
- 5. Generic Object Detection for Industrial Applications
- Difference between recognition, detection, and categorization
- Smartly selecting and preparing application specific training data
- Parameter selection when training an object model
- Using scene specific knowledge and constraints to optimize the detection result
- Obtaining rotation invariance object detection
- 2D scale space relation
- Performance evaluation and GPU optimizations
- Practical applications
- Summary
- 6. Efficient Person Identification Using Biometric Properties
- Biometrics, a general approach
- Face detection and recognition
- Fingerprint identification, how is it done?
- Iris identification, how is it done?
- Combining the techniques to create an efficient people-registration system
- Summary
- 7. Gyroscopic Video Stabilization
- Index
This chapter showed a complete panorama application in Android Studio where OpenCV 3 is used in both the Java interface and the C++ interface with the support of the Native Development Kit (NDK). The chapter also introduced us to how to use the Android Camera API with the OpenCV library. Also, the chapter illustrated some basic implementation with the OpenCV 3 stitching module to perform image stitching.
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