Journal ArticleDOI
A Mathematical Model for Computer Image Tracking
George R. Legters,Tzay Y. Young +1 more
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TLDR
The tracking algorithm is implemented to track moving objects with occasional occlusion in computer-simulated binary images and a variational estimation algorithm is developed to track the dynamic parameters of the operators.Abstract:
A mathematical model using an operator formulation for a moving object in a sequence of images is presented. Time-varying translation and rotation operators are derived to describe the motion. A variational estimation algorithm is developed to track the dynamic parameters of the operators. The occlusion problem is alleviated by using a predictive Kalman filter to keep the tracking on course during severe occlusion. The tracking algorithm (variational estimation in conjunction with Kalman filter) is implemented to track moving objects with occasional occlusion in computer-simulated binary images.read more
Citations
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Journal ArticleDOI
Estimation of Object Motion Parameters from Noisy Images
Ted J. Broida,Rama Chellappa +1 more
TL;DR: An approach is presented for the estimation of object motion parameters based on a sequence of noisy images that may be of use in situations where it is difficult to resolve large numbers of object match points, but relatively long sequences of images are available.
Journal ArticleDOI
Computation and analysis of image motion: a synopsis of current problems and methods
Amar Mitiche,Patrick Bouthemy +1 more
TL;DR: A structured synopsis of the problems in image motion computation and analysis, and of the methods proposed, exposing the underlying models and supporting assumptions are offered.
Journal ArticleDOI
Semiautomatic segmentation and tracking of semantic video objects
Chuang Gu,Ming-Chieh Lee +1 more
TL;DR: A novel semantic video object extraction system using mathematical morphology and a perspective motion model to solve the semantic videoobject extraction problem in two separate steps: supervised I-frame segmentation, and unsupervised P-frame tracking.
Journal ArticleDOI
Fast occluded object tracking by a robust appearance filter
TL;DR: A new method for object tracking in image sequences using template matching that is computationally fast enough to track objects in real time and able to handle abrupt changes of lighting conditions.
Journal ArticleDOI
A maximum likelihood framework for determining moving edges
TL;DR: In this paper, an approach that relies on modeling principles and likely hypothesis testing techniques is proposed for the determination of moving edges in an image sequence, where a spatio-temporal edge is modeled as a surface patch in a 3D spatiotemporal space.
References
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Book
Applied Optimal Estimation
TL;DR: This is the first book on the optimal estimation that places its major emphasis on practical applications, treating the subject more from an engineering than a mathematical orientation, and the theory and practice of optimal estimation is presented.
Journal ArticleDOI
Velocity determination in scenes containing several moving objects
TL;DR: A relationship between the time variation of intensity, the spatial gradient, and velocity has been developed which allows the determination of motion using clustering techniques, and the clustering technique is described.
Journal ArticleDOI
Motion-compensated television coding: Part I
Arun N. Netravali,J. D. Robbins +1 more
TL;DR: Methods of estimating displacements of moving objects from one frame to the next in a television scene and using such displacements for frame-to-frame prediction by a recursive algorithm are presented which make it attractive for hardware implementation.
Journal ArticleDOI
On the Analysis of Accumulative Difference Pictures from Image Sequences of Real World Scenes
Ramesh Jain,H.-h. Nagel +1 more
TL;DR: Analysis of a first-order difference picture (FODP) provides a separate estimate for images of moving objects and of stationary scene components that represents the stationary scene component in a TV-image sequence.
Journal ArticleDOI
Determining the movement of objects from a sequence of images
TL;DR: In this paper, the problem of determining the 3D model and movement of an object from a sequence of two-dimensional images is discussed, and a solution to this problem depends on solving a system of nonlinear equations using a modified least squared error method.
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