Comutations underlying the measuremnt of visual motion.
Artificial Intelligence
Introduction to non-linear optimization
Introduction to non-linear optimization
Robust estimation of three-dimensional motion parameters from a sequence of imag
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of Object Motion Parameters from Noisy Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Finding Trajectories of Feature Points in a Monocular Image Sequence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optical Flow Estimation: An Error Analysis of Gradient-Based Methods with Local Optimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
3-D motion estimation, understanding, and prediction from nosiy image sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion Estimation with More than Two Frames
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reducing "Structure From Motion": A General Framework for Dynamic Vision Part 1: Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Closed Form Solutions for Reconstruction Via Complex Analysis
Journal of Mathematical Imaging and Vision
Unbiased Estimation and Statistical Analysis of 3-D Rigid Motion from Two Views
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human motion estimation from monocular image sequence based on cross-entropy regularization
Pattern Recognition Letters
MDIC '01 Proceedings of the Second International Workshop on Multimedia Databases and Image Communication
Maximum Likelihood Inference of 3D Structure from Image Sequences
EMMCVPR '99 Proceedings of the Second International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Stochastic Approximation and Rate-Distortion Analysis for Robust Structure and Motion Estimation
International Journal of Computer Vision
A sequential algorithm for motion estimation from point correspondences with intermittent occlusions
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol.2)-Volume 2 - Volume 2
Recursive Depth Estimation from a Sequence of Images
ITCC '00 Proceedings of the The International Conference on Information Technology: Coding and Computing (ITCC'00)
Rank 1 Weighted Factorization for 3D Structure Recovery: Algorithms and Performance Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A framework for heading-guided recognition of human activity
Computer Vision and Image Understanding
Filtering image sequences from a moving object and the edge detection problem
Computers & Mathematics with Applications
Machine Vision and Applications
Robot visual servo through trajectory estimation of a moving object using kalman filter
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
Fusing depth and video using rao-blackwellized particle filter
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
Identification of a moving object's velocity with a fixed camera
Automatica (Journal of IFAC)
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The problem considered involves the use of a sequence of noisy monocular images of a three-dimensional moving object to estimate both its structure and kinematics. The object is assumed to be rigid, and its motion is assumed to be smooth. A set of object match points is assumed to be available, consisting of fixed features on the object, the image plane coordinates of which have been extracted from successive images in the sequence. Structure is defined as the 3-D positions of these object feature points, relative to each other. Rotational motion occurs about the origin of an object-centered coordinate system, while translational motion is that of the origin of this coordinate system. In this work, which is a continuation of the research done by the authors and reported previously, results of an experiment with real imagery are presented, involving estimation of 28 unknown translational, rotational, and structural parameters, based on 12 images with seven feature points.