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We propose a novel 6-degree-of-freedom (DoF) visual simultaneous localization and mapping (SLAM) method based on the structural regularity of man-made building environments. The idea is that we use the building structure lines as features for localization and mapping. Unlike other line features, the building structure lines encode the global orientation information that constrains the heading of the...
In this paper, we present a new approach to spatially self-organize a modular artificial skin in 3D space. We were motivated by the demand to efficiently and automatically acquire the position and orientation of a steadily growing number of artificial skin sensor elements. Here, we combine our 3D surface reconstruction algorithm for individual patches of artificial skin, with a common active visual...
In this paper, we present a real time 3D SLAM system for texture-less scenes using only the depth information provided by a low cost RGB-D sensor. The proposed registration method is based on a novel informative sampling scheme that is able to extract the points carrying the most useful information from two consecutive frames. Those points are assigned 3D feature descriptors and matched with their...
We propose a new approach to semantic parsing, which can seamlessly integrate evidence from multiple sensors with overlapping but possibly different fields of view (FOV), account for missing data and predict semantic labels over the spatial union of sensors coverages. The existing approaches typically carry out semantic segmentation using only one modality, incorrectly interpolate measurements of...
Unlike the traditional feature-based methods, we propose using motion vectors (MVs) from video streams as inputs for visual navigation. Although MVs are very noisy and with low spatial resolution, MVs do possess high temporal resolution which means it is possible to merge MVs from different frames to improve signal quality. Homography filtering and MV thresholding are proposed to further improve MV...
In this paper we propose a new way of improving motion estimation based on L-infinity nonlinear minimization. The proposed approach which is a frame to frame motion estimation algorithm for consecutive image stereo pairs is based on three stages. Firstly image processing for detection and match of the remarkable features which are then reconstructed to 3D. Secondarily from the 3D point of cloud an...
In this paper we consider the task of 3D photo visualization using a single monocular image. The main idea is to use single photos taken by capturing devices such as ordinary cameras, mobile phones, tablet PCs etc. and visualize them in 3D on normal displays. Supervised learning approach is hired to retrieve depth information from single images. This algorithm is based on the hierarchical multi-scale...
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