Generation and Adaptation of Transferable Roadway Model for Anticipative Road Following on Satellite-Roadway-Vehicle Network
Kohji Kamejima · SICE Journal of Control Measurement and System Integration · 2011
By matching roadway images in an encountered scene with bird's eye views, the scope of humans' perception is expanded to a satellite-roadway-vehicle network. Based on the geometric consistency of the satellite images with as-is local terrain, in this paper, a computational mechanism is introduced for generation and adaptation of a roadway model transferable through the network. First, the chromatic complexity of the roadway area is represented as a palette of saliency colors via fractal sampling of the scene image. Next, the palette is adapted to the associated area in the bird's eye view. Finally, the palette is transferred to the bird's eye view for anticipatively following the roadway pattern. Experimental results demonstrate that the transferable model can be applied to the extension of the roadway pattern prior to physical access.