Object Matching Using Deformable Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Integral Approach to Free-Form Object Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Determining the Epipolar Geometry and its Uncertainty: A Review
International Journal of Computer Vision
A parametric deformable model to fit unstructured 3D data
Computer Vision and Image Understanding
Teddy: a sketching interface for 3D freeform design
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Pattern Recognition Letters
Image-Based Geometrically-Correct Photorealistic Scene/Object Modeling (IBPhM): A Review
ACCV '98 Proceedings of the Third Asian Conference on Computer Vision-Volume II
Global and local deformations of solid primitives
SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
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In this report, we present a 3D shape modeling method using the shape's silhouettes from multiple views to determine the model (polyhedron) parameters. The polyhedron parameters are determined by neural networks, each of which represents the model's silhouette observed from a view point, and determines the polyhedron parameters by the back propagation algorithm so that the model's silhouette from each view approximates the corresponding silhouette of the target shape. By conducting basic experiments, we verified the effectiveness of the method.