Considering the design principles that traffic signs is to strongly attract the human visual attention, combining the phenomenon that the retina strongly responds to large contrast visual stimulation, a hierarchy saliency analytic framework based on visual contrast is introduced. The authors propose a multi-cue visual attention model for traffic sign detection in street scene, so traffic sign detection and segmentation problem is converted to saliency object discovery and location problem. Experimental results show that the proposed method is better than typical saliency methods.

Based on GeoSOT-3D, a non-overlapping, orthogonal, latitude-longitude consistent grid in the spheroidal space, a true 3D representation method is proposed. The method includes two steps: subdivision preprocessing and subdivision expressing. The experimental result, obtained from using atmospheric data, verifies the feasibility of the method, and it provides a new idea for the representation of global observation data.