Indoor signage detection based on saliency map and bipartite graph matching

Authors:
Shuihua Wang;Yingli Tian
Affiliations:
Department of Electrical Engineering, The City College of New York, NY, 10031, USA;Department of Electrical Engineering, The City College of New York, NY, 10031, USA
Venue:
BIBMW '11 Proceedings of the 2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops
Year:
2011

Citing 0
Cited 1

RGB-D image-based detection of stairs, pedestrian crosswalks and traffic signs

Journal of Visual Communication and Image Representation

Quantified Score

Hi-index	0.00

Visualization

Abstract

Object detection plays a very important role in many applications such as image retrieval, surveillance, robot navigation, wayfinding, etc. In this paper, we propose a novel approach to detect indoor signage to help blind people find their destinations in unfamiliar environments. Our method first extracts the attended areas by using a saliency map. Then the signage is detected in the attended areas by using bipartite graph matching. The proposed method can handle multiple signage detection. Experimental results on our collected indoor signage dataset demonstrate the effectiveness and efficiency of our proposed method. Furthermore, saliency maps could eliminate the interference information and improve the accuracy of the detection results.