Inherent Ambiguities in Recovering 3-D Motion and Structure from a Noisy Flow Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Analysis of Inherent Ambiguities in Recovering 3-D Motion from a Noisy Flow Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape and motion from image streams under orthography: a factorization method
International Journal of Computer Vision
Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Experiments on estimating egomotion and structure parameters using long monocular image sequences
International Journal of Computer Vision - Special issue: image understanding research at the University of Maryland
Reducing "Structure From Motion": A General Framework for Dynamic Vision Part 1: Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Recursive Estimation of Motion, Structure, and Focal Length
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structure from Motion Causally Integrated Over Time
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour Tracking by Stochastic Propagation of Conditional Density
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Comparison of Approaches to Egomotion Computation
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Optimal Structure from Motion: Local Ambiguities and Global Estimates
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Algorithmic and Architectural Design Methodology for Particle Filters in Hardware
ICCD '05 Proceedings of the 2005 International Conference on Computer Design
A 3D Shape Constraint on Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Consistency of robust estimators in multi-structural visual data segmentation
Pattern Recognition
Monte Carlo Based Algorithm for Fast Preliminary Video Analysis
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part I
Statistical Methods and Models for Video-Based Tracking, Modeling, and Recognition
Foundations and Trends in Signal Processing
Efficient particle filtering via sparse kernel density estimation
IEEE Transactions on Image Processing
Note: Bayesian discounting of camera parameter uncertainty for optimal 3D reconstruction from images
Computer Vision and Image Understanding
GFT: GPU fast triangulation of 3D points
ICCVG'10 Proceedings of the 2010 international conference on Computer vision and graphics: Part II
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Fusing depth and video using rao-blackwellized particle filter
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
Enhanced importance sampling: unscented auxiliary particle filtering for visual tracking
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
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In this paper, the structure from motion (SfM) problem is addressed using sequential Monte Carlo methods. A new SfM algorithm based on random sampling is derived to estimate the posterior distributions of camera motion and scene structure for the perspective projection camera model. Experimental results show that challenging issues in solving the SfM problem, due to erroneous feature tracking, feature occlusion, motion/structure ambiguity, mixed-domain sequences, mismatched features, and independently moving objects, can be well modeled and effectively addressed using the proposed method.