Virtual environment generation by CAD-based methodology for underwater vehicle navigation

Perception. We describe a recognition framework to generate a virtual environment through CAD-based vision techniques from optical data. Descriptions of objects of the environment in terms of aspect graphs, and suitable recognition strategies for them are compiled off-line. A relational graph of image features is obtained on-line by processing optical data, and matching occurs between such a graph, and descriptions of objects in the framed scene. Multiresolution techniques are used in order to adapt recognition strategies to the distance and relevance of objects within the field of view.

[1]  Stan Z. Li,et al.  Toward 3D vision from range images: An optimization framework and parallel networks , 1991, CVGIP: Image Understanding.

[2]  Bir Bhanu,et al.  CAD-Based 3D Object Representation for Robot Vision , 1987, Computer.

[3]  Jitendra Malik,et al.  Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Anil K. Jain,et al.  CAD-Based Computer Vision: From CAD Models to Relational Graphs , 1989, IEEE Trans. Pattern Anal. Mach. Intell..