Provided by: University of Alcalá
Date Added: May 2013
Feature vectors can be anything from simple surface normals to more complex feature descriptors. Feature extraction is important in order to solve various computer vision problems: e.g. registration, object recognition and scene understanding. Most of these techniques cannot be computed online due to their complexity and the context where they are applied. Therefore computing these features in real-time for many points in the scene are impossible. In this paper, a hardware-based implementation of 3D feature extraction and 3D object recognition is proposed in order to accelerate these methods and therefore the entire pipeline of RGBD based computer vision systems where such features are typically used.