Experimental tests of vision-based artificial landmark detection using random forests and particle filter
- Authors
- Kim, D.; Lee, D.; Myung, H.; Choi, H.-T.
- Issue Date
- 2014
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Object detection; Particle filter; Random forest; Template matching; Underwater vision
- Citation
- 2014 11th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2014, pp 631 - 634
- Pages
- 4
- Journal Title
- 2014 11th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2014
- Start Page
- 631
- End Page
- 634
- URI
- https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/8691
- DOI
- 10.1109/URAI.2014.7057483
- ISSN
- 0000-0000
- Abstract
- This paper proposes a novel artificial landmark detection technique for underwater robots in structured underwater environment. The novel landmark detection technique is composed of a salient object segmentation using random forest combined with particle filter and an object recognition using weighted template matching. The random image patch-based random forest is employed for detection of the regions of salient objects and its accuracy is enhanced by combining with particle filter. Each detected candidate region is refined through the active contour technique and recognized as one of the artificial landmarks or background by the weighted template matching technique. The performance of the proposed method is evaluated by experiments with an autonomous underwater robot platform, yShark, developed by KRISO and the results are discussed by comparing with the result of the previous research. ? 2014 IEEE.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - ETC > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.