Description

We propose a method which is scalable to the gallery size and modify one-against-all approach to use a tree – based structure. At each internal node of the tree , a binary classifier based on PLS regression is used to guide the search of the matching subject in the gallery. The use of this structure provides substantial reduction in the number of comparisons when a probe sample is matched against the gallery. There are very accurate techniques to perform face identification in controlled environments, particularly when large numbers of samples are available for each face. However, face identification under uncontrolled environments or with a lack of training data is still an unsolved problem.