Wavelet image transformation.

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)

Corners detection using 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.


Regression (Kernel SVM)

Regression with SVMs.

Function regression using (Kernel) Support Vector Machines.


Automating Semantic Mapping of a Document With Natural Language Processing

Natural Language Processing (NLP) intends to enable computers to derive meaning from human or natural language input.  This demonstration extracts entities, keywords, topics, events, themes and concepts.  Other than themes and concepts, the results are essentially keywords or phrases.  The extracted "strings" often have an associated relevance or strength, count or frequency, and/or sentiment value.  We used the features of our NLP Engine to provide some filtering capabilities of RSS feeds, enabling the user to create filters based on the extracted strings and additional values.


Automatic Linguistic Indexing of Pictures

This application demonstrates how computers may be used in intelligent annotation of the audio, video or image media data content.

In this demo experiment we annotated the simple natural image categories. There are 5 ANN classifiers in the project corresponding to:

  • Pictures that might contain animals
  • Pictures that might contain flowers
  • Pictures that might contain landscapes
  • Pictures that might contain sunsets
  • Others pictures that do not contain the above categories or simply unknown image type








unknown category?


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

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