Demonstrates performing image classification using the Bag of Visual Words (BoW) model with SURF features and the Binary Split algorithm.
The BoW model is used to transform the many SURF feature points in a image in a single, fixed-length feature vector. The feature vector is then used to train a Support Vector Machine (SVM) using a variety of kernels.
Handwriting (Multi-class SVM)
Handwritten digits recognition by using Multi-class Kernel Support Vector Machines.
Artificial Neural Networks are a recent development tool that are modeled from biological neural networks. The powerful side of this new tool is its ability to solve problems that are very hard to be solved by traditional computing methods (e.g. by algorithms).
This sample application demonstrates and simulates Artificial Life. The app implements three main technologies which are used in the Gaming industry and Robotics for coding intelligent agents. These are:
- Neural Networks
- Genetic Algorithms
- Steering Behaviours
This demonstration will implement each of these, and demonstrate their usefulness in creating Intelligent Agents.
The algorithms demonstrated are the core of almost every game.
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.
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.
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.