DESIGN AND IMPLEMENTATION ON A FPGA OF A FACIAL RECOGNITION SYSTEM USING “EIGEN FACES”

Automated Facial recognition is a very complex problem due to the many factors that affect the way an image of a person’s face looks. Most of these have no relation to the actual identity of the person. The algorithms used to solve this issue can take advantage of a high level of parallelism and the applications require real time processing. For these reasons, an implementation on hardware is very convenient. In this article, such implementation is presented using a Xilinx Virtex 6 FPGA using one of the most common algorithms, called Eigen Faces

Artificial Intelligence and Cognitive Computing

Artificial intelligence (AI) is a subject garnering increasing attention in both academia and the industry today. The understanding is that AI-enhanced methods and techniques create a variety of opportunities related to improving basic and advanced business functions, including production processes, logistics, financial management and others. As this collection demonstrates, AI-enhanced tools and methods tend to offer more precise results in the fields of engineering, financial accounting, tourism, air-pollution management and many more. The objective of this collection is to bring these topics together to offer the reader a useful primer on how AI-enhanced tools and applications can be of use in today’s world. In the context of the frequently fearful, skeptical and emotion-laden debates on AI and its value added, this volume promotes a positive perspective on AI and its impact on society. AI is a part of a broader ecosystem of sophisticated tools, techniques and technologies, and therefore, it is not immune to developments in that ecosystem. It is thus imperative that inter- and multidisciplinary research on AI and its ecosystem is encouraged. This collection contributes to that