Proceedings Article | 8 May 2010
Proc. SPIE. 7692, Unmanned Systems Technology XII
KEYWORDS: 3D image enhancement, Detection and tracking algorithms, Image processing, Robotics, Navigation systems, Object recognition, Image enhancement, Algorithm development, Robotic systems, 3D image processing
We have developed a framework, Cognitive Object Recognition System (CORS), inspired by
current neurocomputational models and psychophysical research in which multiple recognition
algorithms (shape based geometric primitives, 'geons,' and non-geometric feature-based
algorithms) are integrated to provide a comprehensive solution to object recognition and
landmarking. Objects are defined as a combination of geons, corresponding to their simple parts,
and the relations among the parts. However, those objects that are not easily decomposable into
geons, such as bushes and trees, are recognized by CORS using "feature-based" algorithms. The
unique interaction between these algorithms is a novel approach that combines the effectiveness of
both algorithms and takes us closer to a generalized approach to object recognition. CORS allows
recognition of objects through a larger range of poses using geometric primitives and performs
well under heavy occlusion - about 35% of object surface is sufficient. Furthermore, geon
composition of an object allows image understanding and reasoning even with novel objects. With
reliable landmarking capability, the system improves vision-based robot navigation in GPS-denied
environments. Feasibility of the CORS system was demonstrated with real stereo images captured
from a Pioneer robot. The system can currently identify doors, door handles, staircases, trashcans
and other relevant landmarks in the indoor environment.
