TY - JOUR
T1 - 1-point affine RANSAC for scene image matching in appearance-based localization
AU - Chou, Chih Chung
AU - Wang, Chieh-Chih
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014
Y1 - 2014
N2 - This work aims to improve the matching correctness between scene images, which is the key issue in appearance-based localization tasks. Although existing approaches perform well when the test and map/model images are taken at near places, recognizing far-departed images is still challenging because of the deformed and missing features. In this paper, we propose to predict the type of feature deformation and select the robust features when the camera motion is limited to certain directions. The proposed approach can emphasize the importance of truly robust features in localization tasks. The experimental results shows that the proposed approaches outperforms the state-of-Art matching algorithms, especially in cases of matching distant images.
AB - This work aims to improve the matching correctness between scene images, which is the key issue in appearance-based localization tasks. Although existing approaches perform well when the test and map/model images are taken at near places, recognizing far-departed images is still challenging because of the deformed and missing features. In this paper, we propose to predict the type of feature deformation and select the robust features when the camera motion is limited to certain directions. The proposed approach can emphasize the importance of truly robust features in localization tasks. The experimental results shows that the proposed approaches outperforms the state-of-Art matching algorithms, especially in cases of matching distant images.
UR - http://www.scopus.com/inward/record.url?scp=84939602909&partnerID=8YFLogxK
U2 - 10.1109/CoASE.2014.6899478
DO - 10.1109/CoASE.2014.6899478
M3 - Conference article
AN - SCOPUS:84939602909
SN - 2161-8070
VL - 2014-January
SP - 1194
EP - 1199
JO - IEEE International Conference on Automation Science and Engineering
JF - IEEE International Conference on Automation Science and Engineering
M1 - 6899478
T2 - 2014 IEEE International Conference on Automation Science and Engineering, CASE 2014
Y2 - 18 August 2014 through 22 August 2014
ER -