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The objective of this paper is to propose a new homography-based approach to image-based visual tracking and servoing. The visual tracking algorithm proposed in the paper is based on a new efficient second-order minimization method. Theoretical analysis and comparative experiments with other tracking approaches show that the proposed method has a higher(More)
The tracking algorithm presented in this paper is based on minimizing the sum-of-squared-difference between a given template and the current image. Theoretically, amongst all standard minimization algorithms, the Newton method has the highest local convergence rate since it is based on a second-order Taylor series of the sum-of-squared-differences. However,(More)
Unlike dense stereo, optical flow or multi-view stereo, template-based tracking lacks benchmark datasets allowing a fair comparison between state-of-the-art algorithms. Until now, in order to evaluate objectively and quantitatively the performance and the robustness of template-based tracking algorithms, mainly synthetically generated image sequences were(More)
In this paper we present two efficient GPU-based visual hull computation algorithms. We compare them in terms of performance using image sets of varying size and different voxel resolutions. In addition, we present a real-time 3D reconstruction system which uses the proposed GPU-based reconstruction method to achieve real-time performance (30 fps) using 16(More)
In this paper, we present a complete system for car platooning using visual tracking. The visual tracking is achieved by directly estimating the projective transformation (in our case a homography) between a selected reference template attached to the leading vehicle and the corresponding area in the current image. The relative position and orientation of(More)
This paper addresses the problem of motion estimation and 3-D reconstruction through visual tracking with a single-viewpoint sensor and, in particular, how to generalize tracking to calibrated omnidirectional cameras. We analyze different minimization approaches for the intensity-based cost function (sum of squared differences). In particular, we propose(More)
For a large class of applications, there is time to train the system. In this paper, we propose a learning-based approach to patch perspective rectification, and show that it is both faster and more reliable than state-of-the-art ad hoc affine region detection methods. Our method performs in three steps. First, a classifier provides for every keypoint not(More)
— In this paper, we present a generic and flexible system for vision-based robot control. The system integrates several research areas (visual matching, visual tracking and visual servoing) in a unifying framework. In this framework, the flexibility is obtained using a template matching algorithm based on an efficient second-order minimization. Contrarily(More)
The problem of positioning mobile C-arms, e.g. for down the beam techniques, as well as repositioning during surgical procedures currently requires time, skill and additional radiation. This paper uses a Camera-Augmented Mobile C-arm (CAMC) to speed up the procedure, simplify its execution and reduce the necessary radiation. For positioning the C-arm in(More)