We propose a method for estimating the 3D pose for the camera of a mobile device in outdoor conditions, using only an untextured 2D model. Previous methods compute only a relative pose using a SLAM algorithm, or require many registered images, which are cumbersome to acquire. By contrast, our method returns an accurate, absolute camera pose in an absolute referential using simple 2D+height maps...

Many applications using Virtual Reality (VR) require free hand navigation control. This forbids the use of devices such as Joystick, 3D mouse, ... That is generally because hand-based gesture interaction must be dedicated to specific tasks: sculpting or grasping the objects, which compose a virtual scene. With this aim, we present a polyvalent display approach, which allows the system to determ...

The task of assembling a 3D puzzle can be encountered in a number of problem areas, for instance in fields like cultural heritage or orthopedic surgical planning. In the former the reconstruction of archaeological shards is required, while in the latter fitting of bone fragments has to be accomplished. In the optimal case, this process is carried out automatically. However, at the moment this i...

Simultaneous localization and mapping (SLAM) of working environments is one of the important problems in mobile robotics. For the problem, we present a new method using an omnidirectional stereo system. By using 3D range information obtained from the omnidirectional stereo, we construct scan-matching based extended Kalman filter SLAM(EKF-SLAM) system. In the system, the output of the piecewise ...

This paper presents an LQR-Based 6DOF control of an unmanned aerial vehicles (UAV), namely a small-scale quadrocopter. Due to its high nonlinearity and a high degree of coupling system, the control of an UAV is very challenging. quadrocopter trajectory tracking in a 3D space is greatly affected by the quadrocopter balancing around its roll-pitch-yaw frame. Lack of precise tracking control about...

In this paper we face the issue of fusing 3D data from different sensors in a seamless way, using the unifying framework of uncertain projective geometry. Within this framework it is possible to describe, combine, and estimate various types of geometric elements (2D and 3D points, 2D and 3D lines, and 3D planes) taking their uncertainty into account. Because of the size of the data involved in ...

The letter presents a deep neural network-based method for global and local descriptors extraction from point cloud acquired by rotating 3D LiDAR. can be used two-stage 6DoF relocalization. First, course position is retrieved finding candidates with the closest descriptor in database of geo-tagged clouds. Then, pose between query estimated matching using robust estimator such as RANSAC. Our has...