Paerformance of free-form 3D object recognition from range images

1996 ◽  
Author(s):  
Heinz Huegli ◽  
Christian L. Schutz
Keyword(s):  
Object Recognition ◽  
Free Form ◽  
3D Object Recognition ◽  
Range Images ◽  
3D Object

Rule-based 3D Object Recognition from Range Images

1991 ◽  
Vol 37 (5-6) ◽  
pp. 452-465
Author(s):  
A K Jain ◽  
M D Ramaswami
Keyword(s):  
Object Recognition ◽  
3D Object Recognition ◽  
Range Images ◽  
Rule Based ◽  
3D Object

Multi-scale free-form 3D object recognition using 3D models

2001 ◽  
Vol 19 (5) ◽  
pp. 271-281 ◽  
Author(s):  
F. Mokhtarian ◽  
N. Khalili ◽  
P. Yuen
Keyword(s):  
Object Recognition ◽  
3D Models ◽  
Free Form ◽  
3D Object Recognition ◽  
3D Object ◽  
Scale Free ◽  
Multi Scale

FREE-FORM 3D OBJECT RECOGNITION IN RANGE DATA USING WEAK CORRESPONDENCE BETWEEN LOCAL FEATURES

2003 ◽  
Vol 17 (07) ◽  
pp. 1245-1277
Author(s):  
RICHARD J. CAMPBELL ◽  
PATRICK J. FLYNN
Keyword(s):  
Object Recognition ◽  
Free Form ◽  
3D Object Recognition ◽  
Range Data ◽  
Dense Range ◽  
3D Object ◽  
Number Of Factors ◽  
Potential Applications ◽  
Recognition Systems ◽  
Object Models

Model-Based 3D object recognition systems have a variety of potential applications, but widespread use of such systems has not occurred, due to a number of factors including the representational limitations of models. One historical limitation is the discriminatory representation of free-form objects. The system described in this paper recognizes free-form objects in dense range data acquired by a structured light rangefinder. Images and object models are represented as a network of salient segments which are then brought into correspondence until a reliable pose estimate is available. Experiments with a database of images and object models highlight the contributions of this system.

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