Pattern Rejection

The e ciency of pattern recognition is particularly crucial in two scenarios; whenever there are a large number of classes to discriminate, and, whenever recognition must be performed a large number of times. We propose a single technique, namely, pattern rejection, that greatly enhances e ciency in both cases. A rejector is a generalization of a classi er, that quickly eliminates a large fraction of the candidate classes or inputs. This allows a recognition algorithm to dedicate its e orts to a much smaller number of possibilities. Importantly, a collection of rejectors may be combined to form a composite rejector, which is shown to be far more e ective than any of its individual components. A simple algorithm is proposed for the construction of each of the component rejectors. Its generality is established through close relationships with the Karhunen-Lo eve expansion and Fisher's discriminant analysis. Composite rejectors were constructed for two representative applications, n...

• Type: Conference
• Year: 1996
• Where: CVPR
• Authors: Simon Baker, Shree K. Nayar
• Keywords: Computer Vision, CVPR 1996, Fisher's Discriminant Analysis, Large Number, Pattern Recognition