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Motion tracking in images based on stochastic filters and optimization

Comparison between Kalman and unscented Kalman filters in tracking applications...

In this paper, the problem of tracking feature points along image sequences is addressed. The establishment of correspondences between points and their tracking along image sequences is a complex problem in Computational Vision; especially, when intricate motions, erroneously detections or cases of occlusion or appearance/disappearing of features are involved. To overcome some of those difficulties, a statistic...

Computer Analysis of Objects’ Movement in Image Sequences: Methods and Ap...

Computer analysis of objects’ movement in image sequences is a very complex problem, considering that it usually involves tasks for automatic detection, matching, tracking, motion analysis and deformation estimation. In spite of its complexity, this computational analysis has a wide range of important applications; for instance, in surveillance systems, clinical analysis of human gait, objects recognition...

An Improved Management Model for Tracking Missing Features in Computer Vision L...

In this paper we present a management model to deal with the problem of tracking missing features during long image sequences using Computational Vision. Some usual difficulties related with missing features are that they may be temporarily occluded or might even have disappeared definitively, and the computational cost involved should always be reduced to the strictly necessary. The proposed Net Present Value ...

Efficient Approximation of the Mahalanobis Distance for Tracking with the Kalma...

We address the problem of tracking efficiently feature points along image sequences. To estimate the undergoing movement we use an approach based on Kalman filtering which performs the prediction and correction of the features movement in every image frame. In this paper measured data is incorporated by optimizing the global correspondence set based on efficient approximations of the Mahalanobis distances (MD)....

Simulação da Deformação de Objectos em Imagens segundo Princípios Físicos

Este artigo apresenta uma abordagem física para simular a deformação de objectos representados em imagens. Nessa abordagem, para modelar fisicamente os objectos, é utilizado o método dos elementos finitos. De seguida, é aplicada análise modal para determinar as correspondências entre os nodos dos objectos. Finalmente, o campo dos deslocamentos é simulado através da equação de equilíbrio dinâmico. Para resolver ...

Computer analysis of objects’ movement in image sequences : methods and a...

Computer analysis of objects’ movement in image sequences is a very complex problem, as it usually involves tasks for automatic detection, matching, tracking and deformation estimation. However, this computational analysis has a wide range of important applications; for instance, in surveillance systems, clinical analysis of human gait, objects recognition and deformation analysis. Due to the extent of pu...

An Efficient and Robust Tracking System using Kalman Filter

In this paper we address the problem of tracking features efficiently and robustly along image sequences. To estimate the undergoing movement we use an approach based on Kalman filtering. The measured data is incorporated by optimizing the global correspondence set based on an efficient approximation of the Mahalanobis Distance (MD). Along the image sequence, to deal with the incoming and previously existing fe...

Physical Simulation using FEM, Modal Analysis and the Dynamic Equilibrium Equation

This paper presents a physical approach to simulate objects deformation in images. To physi-cally model the given objects the finite element method is used, and to match the objects’ nodes modal analy-sis is considered. The desired displacement field is estimated through the dynamic equilibrium equation. To solve this differential equation different integration methods can be used. In this paper we presen...

An improved management model for tracking multiple features in long image seque...

In this paper we present a management model to deal with the problem of tracking a large number of features during long image sequences. Some usual difficulties are related to this problem: features may be temporarily occluded or might even have disappeared definitively; the computational cost involved should always be reduced to the strictly necessary. The proposed Net Present Value (NPV) model, based on the e...