Enhancing Face Detection using Bayesian Networks

J. Cândido and M. Marengoni (Brazil)


Face detection, computer vision, Bayesian Networks.


Face detection has been an important research topic over the last 20 years. It is commonly used as a first step in face recognition and several techniques were applied in face detection, going from geometrical methods such as model matching to connectionist methods such as neural networks. This work presents a face detection system that uses a Bayesian Network to combine information from different computational cheap visual operators, and is part of an ongoing project that uses a Web Cam to perform a reliable and accurate eye tracking. The face detection is the first step in this project. The aim in this work is to show that combining simple features in a Bayesian Network it is possible to build an enhanced face detector system, increasing the detection rate and speeding up the face detection process.

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