Bayesian modeling of uncertainty in low-level vision
International Journal of Computer Vision
Subspace methods for recovering rigid motion I: algorithm and implementation
International Journal of Computer Vision
A Three-Frame Algorithm for Estimating Two-Component Image Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape and motion from image streams under orthography: a factorization method
International Journal of Computer Vision
Computing occluding and transparent motions
International Journal of Computer Vision
Affine analysis of image sequences
Affine analysis of image sequences
The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
Recovery of Ego-Motion Using Region Alignment
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matrix computations (3rd ed.)
A Unified Approach to Moving Object Detection in 2D and 3D Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-Frame Estimation of Planar Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical Model-Based Motion Estimation
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Parallax Geometry of Pairs of Points for 3D Scene Analysis
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
From Reference Frames to Reference Planes: Multi-View Parallax Geometry and Applications
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Duality, Rigidity and Planar Parallax
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Model-based brightness constraints: on direct estimation of structure and motion
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Direct Method for Visual Scene Reconstruction
VSR '95 Proceedings of the IEEE Workshop on Representation of Visual Scenes
Factorization with Uncertainty
International Journal of Computer Vision
Keyframe-based tracking for rotoscoping and animation
ACM SIGGRAPH 2004 Papers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-body Factorization with Uncertainty: Revisiting Motion Consistency
International Journal of Computer Vision
An Analysis of Linear Subspace Approaches for Computer Vision and Pattern Recognition
International Journal of Computer Vision
On Single-Sequence and Multi-Sequence Factorizations
International Journal of Computer Vision
Representing Images Using Nonorthogonal Haar-Like Bases
IEEE Transactions on Pattern Analysis and Machine Intelligence
Synchronization of Video Sequences from Free-Moving Cameras
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
Inference of multiple subspaces from high-dimensional data and application to multibody grouping
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
ACM Transactions on Graphics (TOG)
Dense multi-frame optic flow for non-rigid objects using subspace constraints
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
Robust trajectory-space TV-L1 optical flow for non-rigid sequences
EMMCVPR'11 Proceedings of the 8th international conference on Energy minimization methods in computer vision and pattern recognition
3D motion segmentation using intensity trajectory
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part I
Video stabilization using epipolar geometry
ACM Transactions on Graphics (TOG)
Consistent Binocular Depth and Scene Flow with Chained Temporal Profiles
International Journal of Computer Vision
Persistent tracking of static scene features using geometry
Computer Vision and Image Understanding
Hi-index | 0.00 |
When a rigid scene is imaged by a moving camera, the set of all displacements of all points across multiple frames often resides in a low-dimensional linear subspace. Linear subspace constraints have been used successfully in the past for recovering 3D structure and 3D motion information from multiple frames (e.g., by using the factorization method of Tomasi and Kanade (1992, International Journal of Computer Vision, 9:137–154)). These methods assume that the 2D correspondences have been precomputed. However, correspondence estimation is a fundamental problem in motion analysis. In this paper we show how the multi-frame subspace constraints can be used for constraining the 2D correspondence estimation process itself.We show that the multi-frame subspace constraints are valid not only for affine cameras, but also for a variety of imaging models, scene models, and motion models. The multi-frame subspace constraints are first translated from constraints on correspondences to constraints directly on image measurements (e.g., image brightness quantities). These brightness-based subspace constraints are then used for estimating the correspondences, by requiring that all corresponding points across all video frames reside in the appropriate low-dimensional linear subspace.The multi-frame subspace constraints are geometrically meaningful, and are {not} violated at depth discontinuities, nor when the camera-motion changes abruptly. These constraints can therefore replace {heuristic} constraints commonly used in optical-flow estimation, such as spatial or temporal smoothness.