This work addresses the problem of how to capture the dynamics of maneuvering objects for visual tracking. Towards this end, the perspective of recursive Bayesian filters and the perspective of deep learning approaches for state estimation are considered and their functional viewpoints are brought together
We propose a novel method for tracking objects in a video scene that undergo dras-tic changes in the...
In this paper, we consider the problem of tracking multiple maneuvering targets using switching mult...
A model of the world dynamics is a vital part of any tracking algorithm. The observed world can exhi...
This work addresses the problem of how to capture the dynamics of maneuvering objects for visual tra...
Visual tracking represents the basic processing step for most video analytics applications where the...
This thesis deals with state estimation for vehicles that are equipped with various sensors such as ...
Using some form of dynamical model in a visual tracking system is a well-known method for increasing...
The Kalman filter has been used successfully in different prediction applications or state determina...
This thesis deals with state estimation for vehicles that are equipped with various sensors such as ...
Thesis (MSc)--Stellenbosch University, 2021.ENGLISH ABSTRACT: The use of convolutional neural networ...
Accurate and robust tracking of humans is of growing interest in the image processing and computer v...
Self-driving cars need to be able to assess and understand the state of their surroundings. To achie...
In this thesis, a model of motion integration is described which is based on a recursive Bayesian es...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
This paper presents a novel design of visual state estimation for an image-based tracking control sy...
We propose a novel method for tracking objects in a video scene that undergo dras-tic changes in the...
In this paper, we consider the problem of tracking multiple maneuvering targets using switching mult...
A model of the world dynamics is a vital part of any tracking algorithm. The observed world can exhi...
This work addresses the problem of how to capture the dynamics of maneuvering objects for visual tra...
Visual tracking represents the basic processing step for most video analytics applications where the...
This thesis deals with state estimation for vehicles that are equipped with various sensors such as ...
Using some form of dynamical model in a visual tracking system is a well-known method for increasing...
The Kalman filter has been used successfully in different prediction applications or state determina...
This thesis deals with state estimation for vehicles that are equipped with various sensors such as ...
Thesis (MSc)--Stellenbosch University, 2021.ENGLISH ABSTRACT: The use of convolutional neural networ...
Accurate and robust tracking of humans is of growing interest in the image processing and computer v...
Self-driving cars need to be able to assess and understand the state of their surroundings. To achie...
In this thesis, a model of motion integration is described which is based on a recursive Bayesian es...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
This paper presents a novel design of visual state estimation for an image-based tracking control sy...
We propose a novel method for tracking objects in a video scene that undergo dras-tic changes in the...
In this paper, we consider the problem of tracking multiple maneuvering targets using switching mult...
A model of the world dynamics is a vital part of any tracking algorithm. The observed world can exhi...
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