Proc. of the ACM SIGGRAPH/SIGART interdisciplinary workshop on Motion: representation and perception
Processing dynamic image sequences from a moving sensor (artificial intelligence, motion)
Processing dynamic image sequences from a moving sensor (artificial intelligence, motion)
Statistical Analysis of Inherent Ambiguities in Recovering 3-D Motion from a Noisy Flow Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Diffusion Mechanism for Obstacle Detection from Size-Change Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structure From Controlled Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovery of Ego-Motion Using Region Alignment
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Ambiguities in Structure From Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
A General Motion Model and Spatio-Temporal Filters forComputing Optical Flow
International Journal of Computer Vision
A Unified Approach to Moving Object Detection in 2D and 3D Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spatiotemporal Segmentation Based on Region Merging
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ambiguity in Structure from Motion: Sphere versus Plane
International Journal of Computer Vision
An Autonomous Active Vision System for Complete and Accurate 3D Scene Reconstruction
International Journal of Computer Vision
Geometry of Distorted Visual Space and Cremona Transformation
International Journal of Computer Vision
A Multi-Frame Structure-from-Motion Algorithm under Perspective Projection
International Journal of Computer Vision - Special issue on computer vision research at NEC Research Institute
International Journal of Computer Vision - Special issue on image-based servoing
Extracting Structure from Optical Flow Using the Fast Error Search Technique
International Journal of Computer Vision
Optimal Structure from Motion: Local Ambiguities and Global Estimates
International Journal of Computer Vision
On the Sequential Accumulation of Evidence
International Journal of Computer Vision - Special issue: Research at McGill University
Characterizing Depth Distortion under Different Generic Motions
International Journal of Computer Vision
Optimization Criteria and Geometric Algorithms for Motion and Structure Estimation
International Journal of Computer Vision
Understanding the Behavior of SFM Algorithms: A Geometric Approach
International Journal of Computer Vision
3-D Motion Estimation in Model-Based Facial Image Coding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Description and 3-D Reconstruction From Image Trajectories of Rotational Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Projective Structure from Uncalibrated Images: Structure From Motion and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Algebraic Functions For Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optic Flow Field Segmentation and Motion Estimation Using a Robust Genetic Partitioning Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Structure-from-Motion Ambiguity
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Expert: Intelligent Systems and Their Applications
A Three-Dimensional Iconic Environment for Image Database Querying
IEEE Transactions on Software Engineering
Visual Encoding of Tilt from Optic Flow: Psychophysics and Computational Modelling
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Computing the Camera Heading from Multiple Frames
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Optimal Structure from Motion: Local Ambiguities and Global Estimates
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Motion and structure from multiple cues; image motion, shading flow, and stereo disparity
Computer Vision and Image Understanding
Machine Vision and Applications
Structure from Motion Using Sequential Monte Carlo Methods
International Journal of Computer Vision
Estimating Camera Motion through a 3D Cluttered Scene
CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
The least-squares error for structure from infinitesimal motion
International Journal of Computer Vision
Motion Segmentation Using Occlusions
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Parallel Differential Method for Optical Flow Estimation
Journal of Mathematical Imaging and Vision
Automatic scene structure and camera motion using a catadioptric system
Computer Vision and Image Understanding
Optic flow-based vision system for autonomous 3D localization and control of small aerial vehicles
Robotics and Autonomous Systems
Derivation of qualitative information in motion analysis
Image and Vision Computing
Analytical results on error sensitivity of motion estimation from two views
Image and Vision Computing
3-D motion estimation by integrating visual cues in 2-D multi-modal opti-acoustic stereo sequences
Computer Vision and Image Understanding
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Error characteristics of SFM with erroneous focal length
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Mathematical and Computer Modelling: An International Journal
3D Video Based Segmentation and Motion Estimation with Active Surface Evolution
Journal of Signal Processing Systems
A Novel Space Variant Image Representation
Journal of Mathematical Imaging and Vision
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One of the major areas in research on dynamic scene analysis is recovering 3-D motion and structure from optical flow information. Two problems which may arise due to the presence of noise in the flow field are examined. First, motion parameters of the sensor or a rigidly moving object may be extremely difficult to estimate because there may exist a large set of significantly incorrect solutions which induce flow fields similar to the correct one. The second problem is in the decomposition of the environment into independently moving objects. Two such objects may induce optical flows which are compatible with the same motion parameters, and hence, there is no way to refute the hypothesis that these flows are generated by one rigid object. These ambiguities are inherent in the sense that they are algorithm-independent. Using a mathematical analysis, situations where these problems are likely to arise are characterized. A few examples demonstrate the conclusions. Constraints and parameters which can be recovered even in ambiguous situations are presented.