6533b7d7fe1ef96bd1267909
RESEARCH PRODUCT
A Two Stage Neural Architecture for Segmentation and Superquadrics Recovery from Range Data
Roberto PirroneAntonio Chellasubject
Range (mathematics)Artificial neural networkComputer sciencebusiness.industrySuperquadricsComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONFeed forwardScale-space segmentationSegmentationComputer visionArtificial intelligencebusinessdescription
A novel, two stage, neural architecture for the segmentation of range data and their modeling with undeformed superquadrics is presented. The system is composed by two distinct neural networks: a SOM is used to perform data segmentation, and, for each segment, a multilayer feed-forward network performs model estimation.
year | journal | country | edition | language |
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2002-01-01 |