Paper
7 May 2010 Cognitive object recognition system (CORS)
Chaitanya Raju, Karthik Mahesh Varadarajan, Niyant Krishnamurthi, Shuli Xu, Irving Biederman, Troy Kelley
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Abstract
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.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chaitanya Raju, Karthik Mahesh Varadarajan, Niyant Krishnamurthi, Shuli Xu, Irving Biederman, and Troy Kelley "Cognitive object recognition system (CORS)", Proc. SPIE 7692, Unmanned Systems Technology XII, 76920L (7 May 2010); https://doi.org/10.1117/12.853021
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Cited by 7 scholarly publications.
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KEYWORDS
Detection and tracking algorithms

Object recognition

Algorithm development

Image processing

3D image processing

Image enhancement

Navigation systems

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