Using results from robust Kalman filtering, we present a new Kalman filter-based snake model for tracking of nonrigid objects in combined spatio-velocity space. The proposed model is the stochastic version of the velocity snake, an active contour model for combined tracking of position and velocity of nonrigid boundaries. The proposed model uses image gradient and optical flow measurements alon...

Effective detection of vehicles in urban traffic scenes can be achieved by exploiting image analysis techniques. Nevertheless, vehicle detection in daytime and at night can’t be approached with the same image analysis algorithms, due to the strongly different illumination conditions. This paper describes the two different sets of image analysis algorithms that have been used in the VTTS system ...

We introduce a new method for integrated tracking and segmentation of a single non-rigid object in an monocular video, captured by a possibly moving camera. A closed-loop interaction between EM-like color-histogram-based tracking and Random Walker-based image segmentation is proposed, which results in reduced tracking drifts and in fine object segmentation. More specifically, pixel-wise spatial...

We present a three-dimensional (3D) tracker for a clinical ophthalmic spectral domain optical coherence tomography (SD-OCT) system that combines depth-tracking with lateral tracking, providing a stabilized reference frame for 3D data recording and post acquisition analysis. The depth-tracking system is implemented through a real-time dynamic feedback mechanism to compensate for motion artifact ...

Tracking through long image sequences is a fundamental research issue in computer vision. This task relies on estimating correspondences between image pairs over time where error accumulation in tracking can result in drift. In this paper, we propose an optimization framework that utilises a novel Anchor Patch algorithm which significantly reduces overall tracking errors given long sequences co...

In this paper, we investigate the visual tracking problem for robotic systems without image-space velocity measurement, simultaneously taking into account the uncertainties of the camera model and the manipulator kinematics and dynamics. We propose a new image-space observer that exploits the image-space velocity information contained in the unknown kinematics, upon which, we design an adaptive...

In this paper, we build on past efforts with regard to the implementation of an efficient feature tracking algorithm for mass processing satellite images. This generic open-source routine can be applied any type imagery measure sub-pixel displacements between The consists a module (autoRIFT) that enhances computational efficiency and geocoding (Geogrid) mitigates problems found in existing algo...

The goal of this research is to develop a model-based tracking framework with biomedical imaging applications. This is an interdisciplinary area of research with interests in machine vision, image processing, and biology. This thesis presents methods of image modeling, tracking, and data association applied to problems in multi-cellular image analysis, especially hematopoietic stem cell (HSC) i...