Place Recognition using Multiple Feature Types
Shuai Yang*, Wei Mou and Han Wang
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore
- *Corresponding Author:
- Shuai Yang
School of Electrical and Electronic Engineering
Nanyang Technological University
Singapore 639798, Singapore
Tel: +656790 6699
E-mail: [email protected]
Received: November 13, 2015 Accepted: December 11, 2015 Published: December 21, 2015
Citation: Shuai Yang, Wei Mou, Han Wang (2015) Place Recognition using Multiple Feature Types. Adv Robot Autom S2:008. doi: 10.4172/2168-9695.S2-008
Copyright: © 2015 Shuai Yang, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Place recognition has been intensively studied in the context of robot vision. BoW-based approach gains its popularity for its efficiency and robustness using features extracted from images. Many features have been examined in the past for place recognition purpose. However, there is no such feature that can outperform others in all environments. Each feature has its own advantage, thus, they should be carefully chosen depending on the context and environments. In this paper, we propose a modified vocabulary tree with the ability of merging multiple kinds of features such that it allows users to customize different combination of features for better place recognition performance. The system is tested in real-time on real-world datasets and the experiments demonstrates the advantage of our system compared to existing approaches.