TY - GEN
T1 - Suitability analysis based on multi-feature fusion visual saliency model in vision navigation
AU - Jin, Zhen Lu
AU - Pan, Quan
AU - Zhao, Chun Hui
AU - Liu, Yong
PY - 2013
Y1 - 2013
N2 - Matching-area suitability analysis in vision navigation system for unmanned aerial vehicle (UAV) is a very worthy but full of challenges research area. In this paper, a multi-feature fusion based visual saliency model (MFF-VSM) was established by introducing invariant features of speeded-up robust features (SURF) directly into the visual saliency model, based on which the extraction method of suitable matching-areas was proposed. With the integration of cross-scale SURF feature maps in the way we defined, the conspicuity map of SURF channel is obtained. By adding SURF channel into the traditional visual saliency model and fusing multi-feature of SURF, color, intensity and orientation, the MFF-VSM model is proposed. Based on the MFF-VSM, salient locations in sensed map could be obtained and chosen as suitable matching-areas. Simulation results show that the error of image registration with extracted matching-areas based on MFF-VSM meet the demands of vision navigation system. The proposed method may provide new ideas for autonomous navigation of UAV in the future.
AB - Matching-area suitability analysis in vision navigation system for unmanned aerial vehicle (UAV) is a very worthy but full of challenges research area. In this paper, a multi-feature fusion based visual saliency model (MFF-VSM) was established by introducing invariant features of speeded-up robust features (SURF) directly into the visual saliency model, based on which the extraction method of suitable matching-areas was proposed. With the integration of cross-scale SURF feature maps in the way we defined, the conspicuity map of SURF channel is obtained. By adding SURF channel into the traditional visual saliency model and fusing multi-feature of SURF, color, intensity and orientation, the MFF-VSM model is proposed. Based on the MFF-VSM, salient locations in sensed map could be obtained and chosen as suitable matching-areas. Simulation results show that the error of image registration with extracted matching-areas based on MFF-VSM meet the demands of vision navigation system. The proposed method may provide new ideas for autonomous navigation of UAV in the future.
KW - Multi-feature Fusion
KW - Suitability Analysis
KW - SURF
KW - Vision Navigation
KW - Visual Saliency Model
UR - http://www.scopus.com/inward/record.url?scp=84890849472&partnerID=8YFLogxK
M3 - 会议稿件
AN - SCOPUS:84890849472
SN - 9786058631113
T3 - Proceedings of the 16th International Conference on Information Fusion, FUSION 2013
SP - 235
EP - 241
BT - Proceedings of the 16th International Conference on Information Fusion, FUSION 2013
T2 - 16th International Conference of Information Fusion, FUSION 2013
Y2 - 9 July 2013 through 12 July 2013
ER -