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Recognition of dominant planes is an important task used in areas such as robot navigation, augmented reality, 3D reconstruction, among others. There are several approaches for recognizing planar structures, however, most of these approaches are based on processing two or more images captured from different camera views or on processing 3D data in the form of point clouds associated with the camera...
We present a novel methodology that combines stereo vision and parallel processing, based on GPU and the use of binary descriptors, for fast plane extraction. Typical stereo algorithms require an image rectification stage that has to run in a frame-to-frame basis, increasing the computational burden and with the possibility of compromising high frame rate operation. Hence, we propose to use a semi-calibrated...
In this work we address the problem of 3D mapping of environments with large textureless regions, which generates sparse 3D maps that may not represent well the mapped scene. To deal with this problem, we propose to enhance sparse 3D maps by using a superpixel-based segmentation with the aim of generating denser 3D maps of the scene in real time. This can be exploited in virtual reality applications...
Augmented reality combines real footage taken of a scene with virtual elements. However, most current methods rely on camera localisation and 3D reconstruction or point cloud generation in order to integrate augmented reality to the footage. In contrast, in this work we present a novel method to augment virtual reality to the scene based on the recognition of dominant planes in interior scenes. Our...
In this work we present initial results of a system that combines wearable technology and monocular simultaneous localisation and mapping (SLAM) for remote controlling of a low-cost micro aerial vehicle (MAV) that flies beyond the visual line-of-sight. To this purpose, as a first step, we use a state-of-the-art visual SLAM system, called ORB-SLAM, to create a 3D map of the scene. The visual data feeding...
We investigate a new approach to vision based mapping, in which single image structure recognition is used to derive strong priors for initialisation of higher-level primitives in the map. This can reduce state size and speed up the building of more meaningful maps. We focus on plane mapping and use a recognition algorithm to detect and estimate the 3D orientation of planar structures in key frames,...
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