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Part segmentation from stereo
Author(s) -
Chen LiangHua,
Lin WeiChung,
Liao HongYuan Mark
Publication year - 1994
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/ima.1850050304
Subject(s) - segmentation , artificial intelligence , computer science , computer vision , process (computing) , scale space segmentation , segmentation based object categorization , surface (topology) , object (grammar) , image segmentation , minimum spanning tree based segmentation , set (abstract data type) , pattern recognition (psychology) , mathematics , geometry , operating system , programming language
This article addresses the problem of segmenting objects into parts using stereo images. There are three components in the part segmentation process: surface segmentation, region grouping, and volumetric models (superquadrics) recovery/segmentation. The surface segmentation process segments the image into a set of regions such that each region represents a smooth surface. The region grouping process merges the segmented regions into parts. Finally the process of volumetric models recovery/segmentation recovers the part model and segments that part into smaller parts if necessary. Because we use both surface and volumetric models to drive the part segmentation process, we can capture more geometric properties of the object, and the application domain of our approach is broader than that of previous approaches. The performance of the proposed system is demonstrated with real images and synthetic images. Experimental results show that the system is stable and capable of handling a variety of objects.©1994 John Wiley & Sons Inc