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Photo-based augmentation is a growing field in particular for industrial augmented reality (IAR) applications. Registration is at the core of every photo-based AR software. This alignment of the image to the 3D model coordinate system is usually achieved with fiducial markers. When a single keyframe is used, the unknown baseline length has to be estimated in order to superimpose virtual models onto...
In the recent years, many industrial augmented reality (IAR) applications are shifting from video to still images to create a mixed view. This new type of application is called photo-based augmented reality. In order to guarantee the success of these applications, a simple and efficient registration method is required. We present a new method to register an image to a CAD model using a single keyframe...
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 used. The evaluation is therefore often intrinsically...
In this paper, we present an automatic pose estimation (6 DoF) technique to augment images using keyframes pre-registered to a CAD model. State of the art techniques recover the essential matrix (5 DoF) in an automatic manner, but include a manual step to align the image with the CAD reference system because the essential matrix does not provide the scale of the translation. We propose using planar...
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 cameras and 4 PCs.
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 only its identity, but also a first estimate...
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 novel variants of the efficient second-order...
In this paper, a new approach for object detection and pose estimation is introduced. The contribution consists in the conception of entities permitting stable detection and reliable pose estimation of a given object. Thanks to a well- defined off-line learning phase, we design local and minimal subsets of feature points that have, at the same time, distinctive photometric and geometric properties...
We propose a method that dramatically improves the performance of template-based matching in terms of size of convergence region and computation time. This is done by selecting a subset of the template that verifies the assumption (made during optimization) of linearity or quadraticity with respect to the motion parameters. We call these subsets linear or quadratic subsets. While subset selection...
The objective of this paper is to propose a new homography-based approach to image-based visual servoing. The visual servoing method does not need any measure of the 3D structure of the observed target. Only visual information measured from the reference and the current image are needed to compute the task function (isomorphic to the camera pose) and the control law to be applied to the robot. The...
In the last decade, research on vision-based robot control has been concentrated on two main issues: the narrow field of view of the conventional camera and the model dependency of the standard visual servoing approaches. In this paper, we propose a simple and elegant solution to these issues. To enlarge the field of view of the cameras, we use omnidirectional cameras. And to overcome the model dependency...
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