TY - GEN
T1 - Analysis of floor map image in information board for indoor navigation
AU - Honto, Tomoya
AU - Sugaya, Yoshihiro
AU - Miyazaki, Tomo
AU - Omachi, Shinichiro
PY - 2017/11/20
Y1 - 2017/11/20
N2 - Various indoor navigation methods have been developed recently, but digitalized data of indoor map is not always available. Therefore, an indoor navigation framework using an image of information board has been proposed. In this method, the process to extract map regions from the image of an information board is necessary to be done by hands beforehand, and the process to estimate passageway regions is important because its information is used in map matching. However, the method of passageway discrimination is very heuristic, which is intended for a specific type of floor maps. Therefore, in this paper, we propose a semi-automatic method to extract map regions from the image of information board with simple user's operation. We use GrabCut method and Snakes method for the extraction method. In GrabCut method, we detect closed regions to prevent the degradation of accuracy when conducting GrabCut to the downsizing image. The proposed method can extract a map region with few deficits in short calculation time. In addition, we propose a machine learning based method to classify passageway regions and other regions from a segment image. We confirmed that the proposed methods are effective and promising by experiments.
AB - Various indoor navigation methods have been developed recently, but digitalized data of indoor map is not always available. Therefore, an indoor navigation framework using an image of information board has been proposed. In this method, the process to extract map regions from the image of an information board is necessary to be done by hands beforehand, and the process to estimate passageway regions is important because its information is used in map matching. However, the method of passageway discrimination is very heuristic, which is intended for a specific type of floor maps. Therefore, in this paper, we propose a semi-automatic method to extract map regions from the image of information board with simple user's operation. We use GrabCut method and Snakes method for the extraction method. In GrabCut method, we detect closed regions to prevent the degradation of accuracy when conducting GrabCut to the downsizing image. The proposed method can extract a map region with few deficits in short calculation time. In addition, we propose a machine learning based method to classify passageway regions and other regions from a segment image. We confirmed that the proposed methods are effective and promising by experiments.
KW - GrabCut
KW - Machine learning
KW - Map analysis
KW - Snakes
UR - http://www.scopus.com/inward/record.url?scp=85043502692&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85043502692&partnerID=8YFLogxK
U2 - 10.1109/IPIN.2017.8115896
DO - 10.1109/IPIN.2017.8115896
M3 - Conference contribution
AN - SCOPUS:85043502692
T3 - 2017 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2017
SP - 1
EP - 7
BT - 2017 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2017
Y2 - 18 September 2017 through 21 September 2017
ER -