Computational Models of Object Recognition - Goal, Role and Success

Tayyaba Azim

2014

Abstract

This paper surveys the learning algorithms of visual features representation and the computational modelling approaches proposed with the aim of developing better artificial object recognition systems. It turns out that most of the learning theories and schemas have been developed either in the spirit of understanding biological facts of vision or designing machines that provide better or competitive perception power than humans. In this study, we discuss and analyse the impact of notable statistical approaches that map the cognitive neural activity at macro level formally, as well as those that work independently without any biological inspiration towards the goal of developing better classifiers. With the ultimate objective of classification in hand, the dimensions of research in computer vision and AI in general, have expanded so much so that it has become important to understand if our goals and diagnostics of the visual input learning are correct or not. We first highlight the mainstream approaches that have been proposed to solve the classification task ever since the advent of the field, and then suggest some criterion of success that can guide the direction of the future research.

Paper Citation

in Harvard Style

Azim T. (2014). Computational Models of Object Recognition - Goal, Role and Success . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-003-1, pages 179-186. DOI: 10.5220/0004737601790186

in Bibtex Style

@conference{visapp14,
author={Tayyaba Azim},
title={Computational Models of Object Recognition - Goal, Role and Success},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={179-186},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004737601790186},
isbn={978-989-758-003-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)
TI - Computational Models of Object Recognition - Goal, Role and Success
SN - 978-989-758-003-1
AU - Azim T.
PY - 2014
SP - 179
EP - 186
DO - 10.5220/0004737601790186