Author:
Diego Martinoia
Affiliation:
Politecnico di Milano, Italy
Keyword(s):
Gesture Recognition, Invariants, Moments, Shape.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Features Extraction
;
Image and Video Analysis
;
Shape Representation and Matching
Abstract:
Despite Hu’s invariants were proven not to be independent nor complete long time ago, their use in computer vision applications is still broad, mainly because of their diffusion among common CV libraries and ease of use by inexperienced users. In this paper I want to investigate whether, given their mathematical flaws, they are nevertheless good enough to justify such a wide diffusion, also considering that more sophisticated tools have been developed over the years.
In order to do this, I am going to test the robustness of Hu’s invariants in a comparative way against the more modern wavelet invariants, in a hand gesture recognition application. Finally, I am going to discuss, basing my considerations on the experimental data, whether Hu’s invariants are still a viable option for small scale, amateurish applications, or if the time has come to abandon them for more effective solutions.