Kernel based nonlinear Feature Extraction (KFE) or dimensionality reduction is a widely used pre-processing step in pattern classification and data mining tasks. Given a positive...
—Detection of spurious features is instrumental in many computer vision applications. The standard approach is feature based, where extracted features are matched between the ima...
Terascale simulations produce data that is vast in spatial, temporal, and variable domains, creating a formidable challenge for subsequent analysis. Feature extraction as a data r...
We consider feature extraction (dimensionality reduction) for compositional data, where the data vectors are constrained to be positive and constant-sum. In real-world problems, t...
In this paper, we present a novel feature extraction approach based on Curvature Scale Space (CSS) for translation, scale, and rotation invariant recognition of hand poses. First,...