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For over a decade, there has been an increasing interest in face recognition in diverse fields such as pattern recognition, computer vision, telecommunications, video, security and Internet applications, and cognitive psychology.
Among various face recognition algorithms developed, they are mainly classified into two groups: pose dependent and pose invariant. Pose-dependent algorithms rely on two dimensional images of different poses of faces, while pose-invariant techniques are based on three-dimensional models. Here, let us ask a simple question: How does an artist or a caricaturist capture the characteristics of faces and with simple line drawings makes us successfully recognize faces, in many cases better than the full image of a person? If the answer can be found, we may come up with better face recognition methods.
To learn this new perspective of face recognition, please read the column article “Can an Algorithm Recognize Montage Portraits as Human Faces?” by Dr. Tayfun Akgül in the January issue of IEEE Signal Processing Magazine.
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