In Partial Fulfillment of the Requirements for the Degree of
Master of Science
Will defend his thesis
Performing 3D face recognition when only partial 3D data are present in the gallery and probe is a very challenging task. The task is even more challenging when the gallery dataset originates from one side of the face while the probe dataset originates from the other. We present a new method for computing the similarity of partial 3D data for the purpose of face recognition. This method is based on and improves upon Semi-Coupled Dictionary Learning by computing a jointly-optimized solution that incorporates the reconstruction cost, the discrimination cost and the semi-coupling cost. The experiments indicate improvements in recognition performance when compared with existing state-of-the-art methods.
Date: Tuesday, November 20, 2012
Time: 4:00 PM
Faculty, students, and the general public are invited.
Advisor: Prof. Ioannis A. Kakadiaris and Prof. Shishir K. Shah