Title :
A multi-feature integrated visual attention model for matching-area suitability analysis in visual navigation
Author :
Jin Zhenlu ; Pan Quan ; Zhao Chunhui ; Liu Huixia ; Jia Wei
Author_Institution :
Sch. of Autom., Northwestern Polytech. Univ., Xian, China
Abstract :
For matching-area suitability analysis of unmanned aerial vehicle (UAV) visual navigation, a multi-feature integrated visual attention model (MFI-VAM) was established by introducing invariant features, based on which the extraction method of suitable matching-area was proposed. Speeded-up robust features (SURF) were added into visual attention model. The conspicuity map of SURF channel is obtained by cross-scale feature maps integration. Based on multi-feature fusion of SURF, color, intensity and orientation, the MFI-VAM model was built. Salient locations in current map were chosen as suitable matching-areas based on this model. Simulation results show that the image registration error of extracted matching-area based on proposed method is small. This paper could provide new ideas and theoretical guidance for UAV autonomous navigation.
Keywords :
autonomous aerial vehicles; feature extraction; image colour analysis; image fusion; image matching; image registration; mobile robots; path planning; robot vision; MFI-VAM model; SURF channel conspicuity map; UAV autonomous navigation; UAV visual navigation; color feature; cross-scale feature maps integration; image registration error; intensity feature; matching-area suitability analysis; multifeature fusion; multifeature integrated visual attention model; orientation feature; speeded-up robust features; unmanned aerial vehicle; Analytical models; Educational institutions; Electronic mail; Feature extraction; Navigation; Robustness; Visualization; Multi-feature Integrated; UAV; Visual Attention; Visual Navigation; matching-area suitability;
Conference_Titel :
Control Conference (CCC), 2013 32nd Chinese
Conference_Location :
Xi´an
