MEILLAND , Maxime

Abstract

no abstract

This paper proposes a new visual SLAM technique that not only integrates 6 degrees of freedom (DOF) pose and dense structure but also simultaneously integrates the colour information contained in the images over time. This involves developing an inverse model for creating a super-resolution map from many low resolution images. Contrary to...

This paper proposes a new visual SLAM technique that not only integrates 6DOF pose and dense structure but also simultaneously integrates the color information contained in the images over time. This involves developing an inverse model for creating a super-resolution map from many low resolution images. Contrary to classic super-resolution...

Abstract

This paper proposes an approach to real-time dense localisation and mapping that aims at unifying two different representations commonly used to define dense models. On one hand, much research has looked at 3D dense model representations using voxel grids in 3D. On the other hand, image-based key-frame representations for dense environment...

Abstract

National audience

This paper presents a method and apparatus for building 3D dense visual maps of large scale environments for real-time localisation and autonomous navigation. We propose a spherical ego-centric representation of the environment which is able to reproduce photo-realistic omnidirectional views of captured environments. This representation is...

This paper proposes a model for large illumination variations to improve direct 3D tracking techniques since they are highly prone to illumination changes. Within this context dense monocular and multi-camera tracking techniques are presented which each perform in real-time (45Hz). The proposed approach exploits the relative advantages of both...

This paper describes a generic method for vision-based navigation in real urban environments. The proposed approach relies on a representation of the scene based on spherical images augmented with depth information and a spherical saliency map, both constructed in a learning phase. Saliency maps are built by analyzing useful information of...

International audience

Abstract

This paper describes a generic method for vision-based navigation in real urban environments. The proposed approach relies on a representation of the scene based on spherical images augmented with depth information and a spherical saliency map, both constructed in a learning phase. Saliency maps are built by analyzing useful information of...

This paper presents a method and apparatus for building dense visual maps of large scale 3D environments for real-time localisation and navigation. A spherical ego-centric representation of the environment is proposed that is able to reproduce photo-realistic omnidirectional views of captured environments. This representation is novel in that...

Motion blur and rolling shutter deformations both inhibit visual motion registration, whether it be due to a moving sensor or a moving target. Whilst both deformations exist simultaneously, no models have been proposed to handle them together. Furthermore, neither deformation has been considered previously in the context of monocular fullimage...

Acquiring High Dynamic Range (HDR) light-fields from several images with different exposures (sensor integration periods) has been widely considered for static camera positions. In this paper a new approach is proposed that enables 3D HDR environment maps to be acquired directly from a dynamic set of images in real-time. In particular a method...

This paper describes an efficient hybrid laser/vision appearance-based approach to provide a mobile robot with rich 3D information about its environment. By combining the information from an omnidirectional camera and a laser range finder, reliable 3D positioning and an accurate 3D representation of the environment is obtained subject to...

Visual mapping is a required capability for practical autonomous mobile robots where there exists a grow- ing industry with applications ranging from the service to industrial sectors. Prior to map building, Visual Odometry(VO) is an essential step required in the process of pose graph construction. In this work, we first propose to tackle the...

résumé

In this work, a new method is introduced for localization and keyframe identification to solve a Simultaneous Localization and Mapping (SLAM) problem. The proposed approach is based on a dense spherical acquisition system that synthesizes spherical intensity and depth images at arbitrary locations. The images are related by a graph of 6...

In this paper, we draw perspectives to endow a humanoid robot with capabilities to reach known object in an indoor environment by combining continuous monitoring and building using SLAM and visual tracking. We integrates and exploits two key features: object recognition using the toolbox BLORT, and a SLAM (Simultaneous Localization And Mapping)...

We present an assisted navigation scheme designed to control a humanoid robot via a brain computer interface in order to let it interact with the environment and with humans. The interface is based on the well-known steady-state visually evoked potentials (SSVEP) and the stimuli are integrated into the live feedback from the robot embedded...