Computer Vision, Graphics, and Image Processing
Three-dimensional motion computation and object segmentation in a long sequence of stereo frames
International Journal of Computer Vision
The Development and Comparison of Robust Methodsfor Estimating the Fundamental Matrix
International Journal of Computer Vision
Photorealistic Scene Reconstruction by Voxel Coloring
International Journal of Computer Vision
ACM Computing Surveys (CSUR)
Computer Vision: A Modern Approach
Computer Vision: A Modern Approach
Epipolar Geometry in Stereo, Motion, and Object Recognition: A Unified Approach
Epipolar Geometry in Stereo, Motion, and Object Recognition: A Unified Approach
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Unsupervised 3D Object Recognition and Reconstruction in Unordered Datasets
3DIM '05 Proceedings of the Fifth International Conference on 3-D Digital Imaging and Modeling
Photo tourism: exploring photo collections in 3D
ACM SIGGRAPH 2006 Papers
Modeling the World from Internet Photo Collections
International Journal of Computer Vision
Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients
IEEE Transactions on Evolutionary Computation
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It is important to estimate accurate camera parameters in multi-view stereo. In this paper, we use three-view relations, the trifocal tensor, to improve the Bundler, a popular structure from motion (SfM) system, for estimating accurate camera parameters. We propose a novel method: the Robust Orthogonal Particle Swarm Optimization (ROPSO) to estimate a robust and accurate trifocal tensor. In ROPSO, we formulate the trifocal tensor estimation as a global optimization problem and use the particle swarm optimization (PSO) for parameter searching. The orthogonal array is used to select the representative initial particles in PSO for more stable results. In the experiments, we use simulated and real ground truth data for statistical analysis. The experimental results show that the proposed ROPSO can achieve more accurate estimation of the trifocal tensor than the traditional methods and has higher probability to find the optimization solution than the traditional methods. Based on the trifocal tensor estimated by the proposed method, the SfM estimation errors can effectively be reduced. The average reprojection errors are reduced from 21.5 pixels to less than 1 pixel.