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Building a robust and fully automatic framework for human motion tracking in 2D images and videos remains a challenging task in computer vision due to cluttered backgrounds, self-occlusions, variations of body shape and complexities of human postures. In this paper we propose a robust framework for human motion tracking without motion priors. The proposed framework builds an accurate/uncontaminated...
2D articulated human pose tracking in monocular image sequences remains an extremely challenging task due to background cluttering, variation in body appearance, occlusion and imaging conditions. Most of the current approaches only deal with simple appearance and or connected body part dependencies, especially the tree- structured priors assumed over body part connections. Such prior excludes...
We work on the task of 2D articulated human pose tracking in monocular image sequences, an extremely challenging task due to background cluttering, variation in body appearance, occlusion and imaging conditions. Most of current approaches only deal with simple appearance and body part dependencies, especially the Gaussian tree-structured priors assumed over body part connections. Such prior...
The new improved method is based on the magnetic field generating by excitation sources and two sensors sensing. The excitation sources are three orthogonal coils and the coils create the variable magnetic field. The two sensors can receive the information of the magnetic field and they are fixed with an included angle (a constant value less than 90 degree) in order to minimize the size of sensor...
A surgical robot usually utilizes a small marker ball to implement positioning task. However, a tough problem of this system is that images gathered in this system are always distorted, which reduces the accuracy of our positioning. Conventional distortion correction methods have to compute the whole image before determine a certain point's ideal position, which is time consuming and cannot meet the...
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