Global Semantic Description of Objects based on Prototype Theory
Abstract
In this paper, we introduce a novel semantic description approach inspired on Prototype Theory foundations. We propose a Computational Prototype Model (CPM) that encodes and stores the central semantic meaning of objects category: the semantic prototype. Also, we introduce a Prototype-based Description Model that encodes the semantic meaning of an object while describing its features using our CPM model. Our description method uses semantic prototypes computed by CNN-classifications models to create discriminative signatures that describe an object highlighting its most distinctive features within the category. Our experiments show that: i) our CPM model (semantic prototype + distance metric) is able to describe the internal semantic structure of objects categories; ii) our semantic distance metric can be understood as the object visual typicality score within a category; iii) our descriptor encoding is semantically interpretable and significantly outperforms other image global encodings in clustering and classification tasks.
Cite
@article{arxiv.1906.03365,
title = {Global Semantic Description of Objects based on Prototype Theory},
author = {Omar Vidal Pino and Erickson Rangel Nascimento and Mario Fernando Montenegro Campos},
journal= {arXiv preprint arXiv:1906.03365},
year = {2021}
}
Comments
Content: 24 pages (22 + 2 reference) with 15 Figures and 3 Tables. In the future, a new version will be updated with other experiments and results (and a journal reference if applicable)