Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Silhouette and stereo fusion for 3D object modeling
Computer Vision and Image Understanding - Model-based and image-based 3D scene representation for interactive visalization
Multi-View Stereo via Volumetric Graph-Cuts
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A Bayesian method for probable surface reconstruction and decimation
ACM Transactions on Graphics (TOG)
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Combined Depth and Outlier Estimation in Multi-View Stereo
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Multi-View Stereo Reconstruction and Scene Flow Estimation with a Global Image-Based Matching Score
International Journal of Computer Vision
Carved Visual Hulls for Image-Based Modeling
International Journal of Computer Vision
Accurate Camera Calibration from Multi-View Stereo and Bundle Adjustment
International Journal of Computer Vision
SMOTE: synthetic minority over-sampling technique
Journal of Artificial Intelligence Research
Accurate, Dense, and Robust Multiview Stereopsis
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D surface reconstruction using graph cuts with surface constraints
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
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We present a novel algorithm for 3D reconstruction in this paper, converting incremental 3D reconstruction to an optimization problem by combining two feature-enhancing geometric priors and one photometric consistency constraint under the Bayesian learning framework. Our method first reconstructs an initial 3D model by selecting uniformly distributed key images using a view sphere. Then once a new image is added, we search its correlated reconstructed patches and incrementally update the result model by optimizing the geometric and photometric energy terms. The experimental results illustrate our method is effective for incremental 3D reconstruction and can be further applied for large-scale datasets or to real-time reconstruction.