Sciweavers

Share
FGR
2008
IEEE

Face recognition with occlusions in the training and testing sets

8 years 8 months ago
Face recognition with occlusions in the training and testing sets
Partial occlusions in face images pose a great problem for most face recognition algorithms. Several solutions to this problem have been proposed over the years – ranging from dividing the face image into a set of local regions to sophisticated statistical methods. In the present paper, we pose the problem as a reconstruction one. In this approach, each test image is described as a linear combination of the training samples in each class. The class samples providing the best reconstruction determine the class label. Here, “best reconstruction” means that reconstruction providing the smallest matching error when using an appropriate metric to compare the reconstructed and test images. A key point in our formulation is to base this reconstruction solely on the visible data in the training and testing sets. This allows to have partial occlusions in both the training and testing samples, while previous methods only dealt with occlusions in the testing set. We show extensive experime...
Hongjun Jia, Aleix M. Martínez
Added 29 May 2010
Updated 29 May 2010
Type Conference
Year 2008
Where FGR
Authors Hongjun Jia, Aleix M. Martínez
Comments (0)
books