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We introduce a novel hybrid camera configuration composed by a fisheye camera attached to an RGB-D system. Current RGB-D sensors provide the 3D information and scale of the scene, but they are limited by a small field of view. In contrast, wide field of view cameras capture a larger portion of the scene, but providing highly distorted images that require specific algorithms. By coupling a fisheye...
In this paper we present a dense visual odometry system for RGB-D cameras performing both photometric and geometric error minimisation to estimate the camera motion between frames. Contrary to most works in the literature, we parametrise the geometric error by the inverse depth instead of the depth, which translates into a better fit of the distribution of the geometric error to the used robust cost...
One open problem in the fields of place recognition and mapping is to be able to recognise a revisited place when its appearance and layout have changed between visits. In this paper, we investigate this problem in the context of RGB-D mapping in indoor environments. We propose to segment the scene in juts (neighbourhood of 3D points with normals that stick out from the surroundings) and look at low-level...
The projection surface of a 3D line in a non-central camera is a ruled surface, containing the complete information of the 3D line. The resulting line-image is a curve which contains the 4 degrees of freedom of the 3D line. In this paper we investigate the properties of the line-image in conical catadioptric systems. This curve is a particular quartic that can be described by only six homogeneous...
In the last years monocular SLAM has been widely used to obtain highly accurate maps and trajectory estimations of a moving camera. However, one of the issues of this approach is that, due to the impossibility of the depth being measured in a single image, global scale is not observable and scene and camera motion can only be recovered up to scale. This problem gets aggravated as we deal with larger...
The SLAM (Simultaneous Localization and Mapping) problem is one of the essential challenges for the current robotics. Our main objective in this work is to develop a real-time visual SLAM system using monocular omnidirectional vision. Our approach is based on the Extended Kalman Filter (EKF). We use the Spherical Camera Model to obtain geometric information from the images. This model is integrated...
In this paper we present a novel approach to perform indoor self-localization using reference omnidirectional images. We only need one omnidirectional image of the whole scene stored in the robot memory and a conventional uncalibrated on-board camera. We match the omnidirectional image and the conventional images captured by the on-board camera and compute the hybrid epipolar geometry using lifted...
Rock glacier is a rare case of study for 3D modelling. This type of models has particular properties which make it a special application for multi-view stereo reconstruction algorithms. In this work we analyze different types of methods for dense reconstruction from wide base-line views. Besides that we select a method which was adapted and implemented for the specific case of rock glacier modelling...
This paper addresses the problem of vision-based closed-loop control for undulatory robots. We present an image-based visual servoing scheme, which drives the robot to a desired location specified by a target image, without explicitly estimating its pose. Instead, the control relies on the computation of the epipolar geometry between the current and target images. We analyze controllability and stability...
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