Merging virtual objects with the real world: seeing ultrasound imagery within the patient
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
The Use of Dense Stereo Range Data in Augmented Reality
ISMAR '02 Proceedings of the 1st International Symposium on Mixed and Augmented Reality
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
3D Reconstruction of Stereo Images for Interaction between Real and Virtual Worlds
ISMAR '03 Proceedings of the 2nd IEEE/ACM International Symposium on Mixed and Augmented Reality
Spatial Augmented Reality: Merging Real and Virtual Worlds
Spatial Augmented Reality: Merging Real and Virtual Worlds
A Perceptual Matching Technique for Depth Judgments in Optical, See-Through Augmented Reality
VR '06 Proceedings of the IEEE conference on Virtual Reality
Handling Occlusions in Real-time Augmented Reality: Dealing with Movable Real and Virtual Objects
CRV '06 Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision
A markerless registration method for augmented reality based on affine properties
AUIC '06 Proceedings of the 7th Australasian User interface conference - Volume 50
Occlusion detection of real objects using contour based stereo matching
Proceedings of the 2005 international conference on Augmented tele-existence
Estimation of Nonlinear Errors-in-Variables Models for Computer Vision Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Augmented Reality overlaps virtual objects on real world. It mixes a real and virtual world which can generate more semantic meanings than either one. To seamlessly merge virtual and real objects, model registration is an important problem. This paper provides a practical approach to do occlusion registration which is a key cue for users to understand the scene. We apply our method to Video-based Augmented Reality where detecting occlusion relationship is challenging because virtual objects are simply superimposed on images of real scenes. By estimating the dense depth of real objects from stereo, results show our approach can efficiently and correctly register virtual and real objects.