Aleš Leonardis and Aleš Jaklič and Franc Solina (1997) Superquadrics for segmentation and modeling range data. IEEE Transactions on Pattern Recognition and Machine Intelligence, 19 (11). pp. 1289-1295.
We present a novel approach to reliable and efficient recovery of part-descriptions in terms of superquadric models from range data. We show that superquadrics can directly be recovered from unsegmented data, thus avoiding any presegmentation steps (e.g., in terms of surfaces). The approach is based on the recover-andselect paradigm. We present several experiments on real and synthetic range images, where we demonstrate the stability of the results with respect to viewpoint and noise.
|Item Type: ||Article|
|Keywords: ||range image segmentation, recover-and-select paradigm, recovery of volumetric models, superquadrics|
|Language of Content: ||English|
|Related URLs: |
|Institution: ||University of Ljubljana|
|Department: ||Faculty of Computer and Information Science|
|Divisions: ||Faculty of Computer and Information Science > Computer Vision Laboratory|
|Item ID: ||34|
|Date Deposited: ||22 Jan 2003|
|Last Modified: ||13 Dec 2013 07:55|
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