Segmentation through Variable-Order Surface Fitting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Range Image Segmentation Based on Differential Geometry: A Hybrid Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Experimental Comparison of Range Image Segmentation Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast, minimum storage ray-triangle intersection
Journal of Graphics Tools
Edge detection in range images based on scan line approximation
Computer Vision and Image Understanding
A survey of free-form object representation and recognition techniques
Computer Vision and Image Understanding
Edge-Region-Based Segmentation of Range Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Saliency sequential surface organization for free-form object recognition
Computer Vision and Image Understanding
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Segmenting 3D object surfaces is required for various high level computer vision and computer graphics applications. In computer vision, recognizing and estimating poses of 3D objects heavily depend on segmentation results. Similarly, physically meaningful segments of a 3D object may be useful in various computer graphics applications. Therefore, there are many segmentation algorithms proposed in the literature. Unfortunately, most of these algorithms can not perform reliably on free-form objects. In order to segment free-form objects, we introduce a novel method in this study. Different from previous segmentation methods, we first obtain a function representation of the object surface in spherical coordinates. This representation allows detecting smooth edges on the object surface easily by a zero crossing edge detector. Edge detection results lead to segments of the object. We test our method on diverse free-form 3D objects and provide the segmentation results.