There are three examples in the repository.
- Haar Cascade - Object detection face and eye etc.
- Color Detection - Object detection and tracking using object color.
- Template Matching - Object detection with template matching.
- Deep Learning - Object detection with deep neural network (dnn).
Object detection examples with haar cascade classifier algorithm (Face, eyes, mouth, other objects etc.). Cascade Classifier Training http://docs.opencv.org/3.1.0/dc/d88/tutorial_traincascade.html
What is Haar cascade? Haar cascade classifier Object Detection using Haar feature-based cascade classifiers is an effective object detection method proposed by Paul Viola and Michael Jones in their paper, "Rapid Object Detection using a Boosted Cascade of Simple Features" in 2001. It is a machine learning based approach where a cascade function is trained from a lot of positive and negative images. It is then used to detect objects in other images.
Requirements
- OpenCV 3.x Version
- Java >6 Version
Face and eye detection by the camera using haar cascade algorithm.
Video
An example of an application where OpenCV is used to detect objects based on color differences.
Requirements
- OpenCV >2.x Version
- Java >6 Version
Template matching is a technique for finding areas of an image that match (are similar) to a template image (patch).
Requirements
- OpenCV 3.x Version
- Java >6 Version
My blog post for template matching.
- OpenCV > 3.3 Version
In this tutorial you will learn how to use opencv dnn module for image classification by using MobileNetSSD_deploy trained network.
My blog post for DNN.
