Convex-based lightweight feature descriptor for Augmented Reality Tracking

• Published in: PloS one Vol. 19; no. 7; p. e0305199
• Main Authors: S, Indhumathi, Clement J, Christopher
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 18.07.2024; Public Library of Science (PLoS)
• Subjects: Accuracy; Algorithms; Augmented Reality; Biology and Life Sciences; Classification; Computation; Computer and Information Sciences; Convex analysis; Covariance matrix; Efficiency; Eigenvalues; Eigenvectors; Humans; Image enhancement; Image filters; Image Processing, Computer-Assisted - methods; Image retrieval; Invariants; Medicine and Health Sciences; Optimization; Physical Sciences; Polynomials; Recall; Research and Analysis Methods; Robustness (mathematics); Tracking; Unmanned aerial vehicles

Feature description is a critical task in Augmented Reality Tracking. This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. We have developed two filters capable of computing pi...