International audienceWe present a method of using depth information provided by an RGB-D sensor, for visual simultaneous localization and mapping (SLAM), in order to improve its accuracy. We present a constraint bundle adjustment which allows to easily combine depth and visual data in cost function entirely expressed in pixel. The proposed approach is evaluated on a public benchmark dataset and compared to the state of art methods
Simultaneous Localization and Mapping (SLAM) is the problem of localizing a sensor in a map that is ...
We present a new simultaneous localization and mapping SLAM system capable of producing high-quality...
A rising popularity of RGBD sensors caused an increase of research in recording and reconstruction o...
International audienceWe present a method of using depth information provided by an RGB-D sensor, fo...
A key component of Simultaneous Localization and Mapping (SLAM) systems is the joint optimization of...
In the study of SLAM problem using an RGB-D camera, depth information and visual information as two ...
Recently RGB-D sensors have become very popular in the area of Simultaneous Localisation and Mapping...
International audienceSeveral works have focused on Simultaneous Localization and Mapping (SLAM), wh...
Currently, feature-based visual Simultaneous Localization and Mapping (SLAM) has reached a mature st...
Simultaneous Localization and Mapping (SLAM) plays an important role in navigation and augmented rea...
International audienceIn this paper we propose to improve the localization and the 3D mapping provid...
A multi-camera dense RGB-D SLAM (simultaneous localization and mapping) system has the potential bot...
International audienceThis paper describes an extension of the popular simultaneous localisation and...
Simultaneous Localization and Mapping (SLAM) is a process of building a map of an unknown environmen...
Simultaneous Localization and Mapping is a key requirement for many practical applications in robot...
Simultaneous Localization and Mapping (SLAM) is the problem of localizing a sensor in a map that is ...
We present a new simultaneous localization and mapping SLAM system capable of producing high-quality...
A rising popularity of RGBD sensors caused an increase of research in recording and reconstruction o...
International audienceWe present a method of using depth information provided by an RGB-D sensor, fo...
A key component of Simultaneous Localization and Mapping (SLAM) systems is the joint optimization of...
In the study of SLAM problem using an RGB-D camera, depth information and visual information as two ...
Recently RGB-D sensors have become very popular in the area of Simultaneous Localisation and Mapping...
International audienceSeveral works have focused on Simultaneous Localization and Mapping (SLAM), wh...
Currently, feature-based visual Simultaneous Localization and Mapping (SLAM) has reached a mature st...
Simultaneous Localization and Mapping (SLAM) plays an important role in navigation and augmented rea...
International audienceIn this paper we propose to improve the localization and the 3D mapping provid...
A multi-camera dense RGB-D SLAM (simultaneous localization and mapping) system has the potential bot...
International audienceThis paper describes an extension of the popular simultaneous localisation and...
Simultaneous Localization and Mapping (SLAM) is a process of building a map of an unknown environmen...
Simultaneous Localization and Mapping is a key requirement for many practical applications in robot...
Simultaneous Localization and Mapping (SLAM) is the problem of localizing a sensor in a map that is ...
We present a new simultaneous localization and mapping SLAM system capable of producing high-quality...
A rising popularity of RGBD sensors caused an increase of research in recording and reconstruction o...