Three-dimensional object recognition
ACM Computing Surveys (CSUR) - Annals of discrete mathematics, 24
3-D Surface Solution Using Structured Light and Constraint Propagation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing solid objects by alignment with an image
International Journal of Computer Vision
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
A computational approach for corner and vertex detection
International Journal of Computer Vision
Visual learning and recognition of 3-D objects from appearance
International Journal of Computer Vision
3D object recognition using invariance
Artificial Intelligence - Special volume on computer vision
The extremal mesh and the understanding of 3D surfaces
International Journal of Computer Vision
COSMOS-A Representation Scheme for 3D Free-Form Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Point Signatures: A New Representation for 3D Object Recognition
International Journal of Computer Vision
Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of free-form object representation and recognition techniques
Computer Vision and Image Understanding
Object Surface Reconstruction from One Camera System
FGIT '09 Proceedings of the 1st International Conference on Future Generation Information Technology
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This paper deals with the 3D Free form object pose recovering problem that is present in several industrial applications, such as online quality control in production as well as image systems for assembly/welding, augmented reality and robotics. The method presented here uses a structured light based vision system to reconstruct several accurate local 3D patches of the objects. A robust subpixel method for image features detection has been developed in order to increase 3D reconstruction accuracy. The Curvature method is then used to compute a geometric invariant "footprint" to discriminate reconstructed patches, which allows to match them with the object's model. Pose recovering is performed by using the prediction - verification hypotheses paradigm. Some experimental results are given to show the efficiency of the proposed solution when applied to a complex free form object.