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This project aims at studying correlation techniques for facial recognition. We explore some commonly used filters for pattern recognition using convolution and image processing techniques in order to perform subject identification. In addition, we would like to use IR imaging in order to mesure temperature of a subject.
The main objective of the project is to perform subject identification using correlation techniques. In this project we aim at exploring two techniques: MACE filtering and Composite Filtering. Those techniques are based on a simple principle. A database of images is acquired, and a filter is devised in the image frequency domain so that matching is performed via correlation.
The fundamental references of the project are:
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[2]. Composite versus multichannel binary phase-only filtering. de la Tocnaye, Quemener & Petillot.
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[3]. A Technique for Optically Convolving Two Functions. C. S. Weaver and J. W. Goodman
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[4]. Signal detection by complex spatial filtering. A. V. Lugt
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[5]. Face Verification using Correlation Filters. Kumar et. Al.
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[6]. MACE Correlation Filter Algorithm for Face Verification ni Surveillance. Omidora et. Al.
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[8]. New Perspectives in face Correlation Research: A Tutorial. Wang et. Al