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SBA: A software package for generic sparse bundle adjustment
TLDR
Bundle adjustment constitutes a large, nonlinear least-squares problem that is often solved as the last step of feature-based structure and motion estimation computer vision algorithms . Expand
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Efficient model-based 3D tracking of hand articulations using Kinect
TLDR
In this paper, we propose a novel model-based approach to the problem of 3D tracking of hand articulations which is formulated as an optimization problem that minimizes the discrepancy between the 3D structure and appearance of hypothesized instances of a hand model and actual hand observations. Expand
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Full DOF tracking of a hand interacting with an object by modeling occlusions and physical constraints
TLDR
We formulate an optimization problem whose solution is the 26-DOF hand pose together with the pose and model parameters of the manipulated object. Expand
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Real-Time Tracking of Multiple Skin-Colored Objects with a Possibly Moving Camera
TLDR
This paper presents a method for tracking multiple skin- colored objects in images acquired by a possibly moving camera. Expand
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Tracking the articulated motion of two strongly interacting hands
TLDR
We propose a method that relies on markerless visual observations to track the full articulation of two hands that interact with each-other in a complex, unconstrained manner. Expand
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Is Levenberg-Marquardt the most efficient optimization algorithm for implementing bundle adjustment?
TLDR
This paper argues that considerable computational benefits can be gained by substituting the sparse Levenberg-Marquardt algorithm in the implementation of bundle adjustment with a sparse variant of Powell's dog leg non-linear least squares technique. Expand
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Markerless and Efficient 26-DOF Hand Pose Recovery
TLDR
We present a novel method that, given a sequence of synchronized views of a human hand, recovers its 3D position, orientation and full articulation parameters. Expand
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Head pose estimation on depth data based on Particle Swarm Optimization
TLDR
We propose a method for human head pose estimation based on images acquired by a depth camera based on 3D structure information provided by depth cameras. Expand
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FIRE: Fundus Image Registration dataset
Purpose: Retinal image registration is a useful tool for medical professionals. However, performance evaluation of registration methods has not been consistently assessed in the literature. ToExpand
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