Regression (Kernel SVM)
Function regression using (Kernel) Support Vector Machines.
Real-Time Tracking Of Human Eyes Using a Camera
Eyes are the most important features of the human face. So effective usage of eye movements as a communication technique in user-to-computer interfaces can find place in various application areas.
Eye tracking and the information provided by the eye features have the potential to become an interesting way of communicating with a computer in a human-computer interaction (HCI) system. So with this motivation, designing a real-time eye feature tracking software is the aim of this project.
The purpose of this demonstration is to implement a real-time eye-feature tracker with the following capabilities:
- RealTime face tracking with scale and rotation invariance
- Tracking the eye areas individually
- Tracking eye features
- Eye gaze direction finding
- Remote controlling using eye movements
Mouse Control via Webcam
This application image processing, through which we try to recognize hand gestures and control mouse using these gestures. In this app, cursor movement is controlled by the movement of hand and click events are triggered using hand gestures.
Corners detection (FAST)
Demonstrates how to perform corners detection using the FAST corners detector. As the name implies, the FAST detector is one of the fastest corners detectors available in the framework.
The Wavelet sample application shows how to use the Wavelet transform filter to process images using wavelet transforms such as the Haar and CDF9/7.
Handwriting (Multi-class SVM)
Handwritten digits recognition by using Multi-class Kernel Support Vector Machines.