Jehoon Lee

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In this paper, we address the problem of 2D-3D pose estimation. Specifically, we propose an approach to jointly track a rigid object in a 2D image sequence and to estimate its pose (position and orientation) in 3D space. We revisit a joint 2D segmentation/3D pose estimation technique, and then extend the framework by incorporating a particle filter to(More)
In this paper, we propose an approach for tracking an object of interest based on 3-D range data. We employ particle filtering and active contours to simultaneously estimate the global motion of the object and its local deformations. The proposed algorithm takes advantage of range information to deal with the challenging (but common) situation in which the(More)
Constrained registration is an active area of research and is the focus of this work. This note describes a non-rigid image registration framework for incorporating landmark constraints. Points that must remain stationary are selected, the user chooses the spatial extent of the inputs, and an automatic step computes the deformable registration, respecting(More)
This note introduces a model-free and marker-less approach for human body tracking based on a dynamic color model and geometric information of a human body from a monocular video sequence. A multivari-ate Gaussian distribution is learned online from sequential frames to represent the non-stationary color distribution. Images are first filtered according to(More)
This work presents a deformable point set registration algorithm that seeks an optimal set of radial basis functions to describe the registration. A novel, global optimization approach is introduced composed of simulated annealing with a particle filter based generator function to perform the registration. It is shown how constraints can be incorporated(More)
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