Iterative Multi-Planar Camera Calibration: Improving stability using Model Selection

Colloque avec actes et comité de lecture. internationale.International audienceTracking, or camera pose determination, is the main technical challenge in numerous applications in computer vision and especially in Augmented Reality. However, pose computation processes commonly exhibit some fluctuations and lack of precision in the estimation of the parameters. This leads to unpleasant visual impressions when augmented scenes are considered. In this paper, we propose an efficient and reliable method for real time camera tracking which avoid unpleasant statistical fluctuations. This method is based on the knowledge of a piecewise planar structure in the scene and makes use of model selection to reduce fluctuations. Videos are attached to this paper which prove the effectiveness of our approach

Efficient Model-Based Object Pose Estimation Based on Multi-Template Tracking and PnP Algorithms

[[abstract]]Three-Dimensional (3D) object pose estimation plays a crucial role in computer vision because it is an essential function in many practical applications. In this paper, we propose a real-time model-based object pose estimation algorithm, which integrates template matching and Perspective-n-Point (PnP) pose estimation methods to deal with this issue efficiently. The proposed method firstly extracts and matches keypoints of the scene image and the object reference image. Based on the matched keypoints, a two-dimensional (2D) planar transformation between the reference image and the detected object can be formulated by a homography matrix, which can initialize a template tracking algorithm efficiently. Based on the template tracking result, the correspondence between image features and control points of the Computer-Aided Design (CAD) model of the object can be determined efficiently, thus leading to a fast 3D pose tracking result. Finally, the 3D pose of the object with respect to the camera is estimated by a PnP solver based on the tracked 2D-3D correspondences, which improves the accuracy of the pose estimation. Experimental results show that the proposed method not only achieves real-time performance in tracking multiple objects, but also provides accurate pose estimation results. These advantages make the proposed method suitable for many practical applications, such as augmented reality.[[notice]]補正完

Visor de Realidad Aumentada en Museos (RAM) para Exposiciones Situadas en Entornos Cerrados

[ES] La realidad aumentada es una tecnología que ha evolucionado en gran medida en los últimos tiempos. La excelente característica de integración entre el mundo real y el virtual convierten a la realidad aumentada en un elemento óptimo para la utilización de modelos 3D en escenarios reales. El Visor de Realidad Aumentada para Museos es un sistema interactivo que permite al visitante integrar en tiempo real los contenidos virtuales sobre los restos o ruinas de una exposición. A medida que el visitante orienta el visor, se realiza un tracking de la posición y perspectiva de la cámara, permitiendo al modelo 3D conservar la misma perspectiva que la del entorno real. Este artículo describe el concepto, arquitectura y tecnología empleada en este dispositivo así como las técnicas de procesado, renderizado y control empleadas.[EN] Augmented reality has been increasingly used for the last 10 years. Real and virtual world combination supported by this technology has made augmented reality become an essential element for computer generated data integration in real-world. Museum augmented Reality Viewfinder is an interactive system that allows visitors to overlay computer generate contents onto sites and archaeological exhibitions in real time. As the person move the camera around, the position and orientation of the camera perspective is tracked, allowing the overlaid material to remain tied to the physical world. This paper describes concept, architecture and technology inside the Museum augmented Reality Viewfinder, image processing, rendering and PTZ control techniques are also detailed.Flores Gutiérrez, M.; Rufete Martínez, T.; Macanás Vidal, J.; Martínez García, J.; López Martínez, CM.; Ramos Martínez, F. (2011). Visor de Realidad Aumentada en Museos (RAM) para Exposiciones Situadas en Entornos Cerrados. Virtual Archaeology Review. 2(3):87-91. https://doi.org/10.4995/var.2011.4619OJS879123T. Drummond and R. Cipolla (1999): "Real-time tracking of complex structures for visual servoing". In Workshop on Vision Algorithms, pp 69-84.G. Fernandez Navarro,(2009): "Museos de ciencia Interactivos", en Revista de Museología, pp. 22-23.M. Haller, W. Hartmann, T. Luckeneder, J. Zauner (2002): "Combining ARtoolkit with scene graph libraries". Augmented Reality Toolkit, The First IEEE International Workshop, 2pp. http://dx.doi.org/10.1109/art.2002.1106978W. Hoff, T. Lyon, K. Nguyen (1996): "Computer vision based registration techniques for augmented reality". Volume 2904, págs 538-548. Proc. of Intelligent Robots and Computer Vision XV, In Intelligent Systems and Advanced Manufacturing, SPIE, pp 19-21.H. Kato and M. Billinghurts (1999): "Marker tracking and hmd calibration for a video-based augmented reality conferencing system". In IWAR: Proceedings o the 2nd IEEE and ACM International Workshop on Augmented Reality, pp 85, Washinton, DC, USA, Octubre 1999. IEEE Computer Society. http://dx.doi.org/10.1109/IWAR.1999.803809T. Miyashita, P. Meier, T. Tachikawa, S. Orlic, T. Eble, V. Scholz, A. Gapel, O. Gerl, S. Arnaudov, S. Lieberknecht (2008): "An augmented Reality Guide". Symposium on Mixed and Augmented Reality archive Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality table of contents , pp 103-106.N. Mourkoussis, F. Liarokapis, J. Darcy, M. Pettersson, P. Petridis, P.F. Lister, M. White (2002), "Virtual and Augmented Reality Applied to Educational and Cultural Heritage Domains", Proc. Business Applications of Virtual Reality, BAVR 2002 - Workshop on Business Applications of Virtual Reality, Poznan, Poland, April 24-25, pp 367-372. ISBN: 83-916842-0-2.PLETINCKX, Daniel et al. (2004): "Telling the local story: an interactive cultural presentation system for community and regional settings", en Proceedings of the 5th International Symposium on Virtual Reality, Archaeology, and Cultural Heritage, VAST 2004. pp. 233-239.J. Santan Mestre, Joan - F.X. Hernández Cardona (2006) "Museología Crítica", Ediciones Trea, Gijón, España.D.Striker (2002), "Personalized Augmented Reality Touring of Archaeological Sites with Wearable and Mobile Computers" ISWC Proceedings of the 6th IEEE International Symposium on Wearable Computers. 2002.A. Webster, S, Freiner, B. MacIntyre,(1996) et al "Augmented Reality in architectural construction, inspection and renovation." Proc ASCE Thid Congress on Computing in Civil Engineering, Anaheim, CA, June 17-19,pp 913-919,1996.R. Wojciechowski, K. Walczak, M. White, W. Cellary (2004): Building Virtual and Augmented Reality museum exhibitions. Proceedings of the ninth international conference on 3D Web technology, Monterey, California. Pp. 135-144. http://dx.doi.org/10.1145/985040.985060Michael Zoellner, Jens Keil, Timm Drevensek, Harald Wuest,(2009) "Cultural Heritage Layers: Integrating Historic Media in Augmented Reality," vsmm, pp 193-196, 15th International Conference on Virtual Systems and Multimedia. http://dx.doi.org/10.1109/vsmm.2009.3

The Evolution of First Person Vision Methods: A Survey

The emergence of new wearable technologies such as action cameras and smart-glasses has increased the interest of computer vision scientists in the First Person perspective. Nowadays, this field is attracting attention and investments of companies aiming to develop commercial devices with First Person Vision recording capabilities. Due to this interest, an increasing demand of methods to process these videos, possibly in real-time, is expected. Current approaches present a particular combinations of different image features and quantitative methods to accomplish specific objectives like object detection, activity recognition, user machine interaction and so on. This paper summarizes the evolution of the state of the art in First Person Vision video analysis between 1997 and 2014, highlighting, among others, most commonly used features, methods, challenges and opportunities within the field.Comment: First Person Vision, Egocentric Vision, Wearable Devices, Smart Glasses, Computer Vision, Video Analytics, Human-machine Interactio