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[资源] Invariant surface characteristics for 3D object recognition in range images.1986

3D计算机视觉、距离图像处理领域的奠基性经典论文。

Paul J. Besl, Ramesh C. Jain. Invariant surface characteristics for 3D object recognition in range images[J]. Computer Vision, Graphics, and Image Processing, 1986. 33(1): 33-80. doi: 10.1016/0734-189X(86)90220-3.

Abstract:
In recent years there has been a tremendous increase in computer vision research using
range images (or depth maps) as sensor input data. The most attractive feature of range images
is the explicitness of the surface information. Many industrial and navigational robotic tasks
will be more easily accomplished if such explicit depth information can be efficiently obtained
and interpreted. Intensity image understanding research has shown that the early processing of
sensor data should be data-driven. The goal of early processing is to generate a rich description
for later processing. Classical differential geometry provides a complete local description of
smooth surfaces. The first and second fundamental forms of surfaces provide a set of
differential-geometric shape descriptors that capture domain-independent surface information.
Meun curvature and Guussian curvuture are the fundamental second-order surface characteristics
that possess desirable invariance properties and represent extrinsic and intrinsic surface
geometry respectively. The signs of these surface curvatures are used to classify range image
regions into one of eight basic viewpoint-independent surface types. Experimental results for
real and synthetic range images show the properties, usefulness, and importance of
differential-geometric SurfaCe characteristics,

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