An implementation and limited extension of a traffic sign recognition method based on the work by [1] is presented here. This implementation can be extended to target real-time detection. Yield sign, stop sign and red-bordered circular signs are considered. First, image is color segmented based on a thresholding technique. Then, corner features are detected using convolution masks (based on wor...

Working Tomorrow / Business Unit Technical Software Engineering Faculty of Electrical Engineering, Mathematics and Computer Science CE-MS-2006-04 Currently emerging flat plasma and LCD television sets, provide a higher resolution and better color quality than the conventional CRT TVs. To fully utilize the capabilities of these displays, Standard Definition video material need to be enhanced in ...

Prolonged exposure to stress can cause serious mental and physical illnesses. Therefore, it is important that people are aware of stressful situations, so that they can take necessary actions to cope with them. We introduce a mobile system that is able to detect stress in individuals in real-time based on electrocardiogram and electrodermal activity. The system is built around an Android smartp...

Government agencies, personnel security professionals, and our military services are faced with new challenges to rapidly assess the credibility of statements made by individuals in airports, border crossings, secured facilities, and a variety of environments not conducive to prolonged interviews. The changing environment has become more global and threats lie not just in the securing of an env...

Real-time, scalable, multi-view object detection is an active area of research, particularly in robot vision community. An efficient template-based object detection algorithm has recently been proposed [1] that utilizes both color and depth information, and works on texture-less objects. However, the approach scales linearly with the number of objects and views. This project explores a variatio...

This paper describes a visual object detection framework that is capable of processing images extremely rapidly while achieving high detection rates. There are three key contributions. The first is the introduction of a new image representation called the “Integral Image” which allows the features used by our detector to be computed very quickly. The second is a learning algorithm, based on Ada...

In this work, we address the problem of real-time action recognition from video streams, in particular exploiting the information given by repetitive actions. Adapting the SPRING algorithm, a sequential variant of dynamic time warping (DTW), not only single frames can be classified but also repetitions of actions can be recognized. These particular benefits are demonstrated for two different pu...

This paper examines real-time intrusion detection systems. Intrusion detection systems detect attacks that attempt to compromise the integrity, confidentiality, or availability of a resource [1]. In particular, this paper focuses on intrusion detection approaches, techniques, and systems.

This study presents a novel Hybrid Intelligent Intrusion Detection System (IDS) known as RT-MOVICAB-IDS that incorporates temporal control. One of its main goals is to facilitate real-time Intrusion Detection, as accurate and swift responses are crucial in this field, especially if automatic abortion mechanisms are running. The formulation of this hybrid IDS combines Artificial Neural Networks ...