In this paper we present a novel boosting algorithm for supervised learning that incorporates invariance to data transformations and has high generalization capabilities. While on...
We present a novel approach to reconstruction based superresolution that explicitly models the detector's pixel layout. Pixels in our model can vary in shape and size, and th...
We address the problem of reconstructing the 3-D shape of a Lambertian surface from multiple images acquired as an object rotates under distant and possibly varying illumination. ...
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. The projection vectors are commonly obtained by maximizing ...
This paper presents a technique for determining an object's shape based on the similarity of radiance changes observed at points on its surface under varying illumination. To...