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Feature Extraction on Range Images – A New Approach

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Coleman, SA, Scotney, BW and Suganthan, S (2007) Feature Extraction on Range Images – A New Approach. In: IEEE International Conference on Robotics and Automation , Rome. IEEE RAS. 6 pp. [Conference contribution]

Full text not available from this repository.

DOI: 10.1109/ROBOT.2007.363131

Abstract

Range images can provide an almost 3-dimensional description of a scene. Feature driven segmentation of range images has been primarily used for 3D object recognition, and hence the accuracy of the detected features is a prominent issue. Feature extraction on range images has proven to be a more complex problem than on intensity images due to both the irregular distribution of range image data and the nature of the features that are present in range images. Approaches to range image feature extraction are often scan line based approximations that carry a significant computational overhead and hence are not appropriate for real-time processing. This paper presents a design procedure for scalable first order derivative operators that can be used directly on irregularly distributed data. Hence the method is appropriate for direct use on range image data without the requirement of image preprocessing and could form the basis of algorithms of real-time robotic applications.

Item Type:Conference contribution (Paper)
Keywords:range images, feature extraction
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Information Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:6833
Deposited By:Professor Bryan Scotney
Deposited On:23 May 2011 15:42
Last Modified:23 May 2011 15:42

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