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This work aims to realize a recognition system for markerless tracking in mobile augmented reality. A method based local invariant descriptors is implemented to extract image feature points for natural fiducial identification. This technique is optimized and adapted for a mobile architecture with low resources and deployed on a portable device. Afterwards,(More)
This paper describes a multimodal tracking system to resolve occlusions in augmented reality applications. The first module of the proposed architecture is composed of a vision based system and allows identification and tracking of visible targets. When targets are partially occluded by scene elements, a second module relieves the vision based module and(More)
In this work we present a novel interaction approach based on a gesture recognition system using a Microsoft Kinect sensor. Gestures are defined and interpreted in order to activate controls on a media device. This natural interface enables intuitive interaction with the multimedia content. The depth sensor observes the scene to detect a request for control(More)
This paper describes the ongoing developments in Photogrammetry and Mixed Reality for the Venus European project (Virtual ExploratioN of Underwater Sites, http://www.venus-project.eu). The main goal of the project is to provide archaeologists and the general public with virtual and augmented reality tools for exploring and studying deep underwater(More)
Special Issue of Virtual Reality " Virtual Reality and Culture Technology " manuscript No. Abstract The paper presents different issues dealing with both the preservation of cultural heritage using Virtual Reality (VR) and Augmented Reality (AR) technologies in a cultural context. While the VR/AR technologies are mentioned, the attention is paid to the 3D(More)
This paper presents a natural feature tracking system for object recognition in real-life environments. The system is based on a local keypoint descriptor method optimized and adapted to extract salient regions within the image. Each object in the gallery is characterized by keypoints and corresponding local descriptors. The method first identifies gallery(More)