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Online Robust 3D Mapping Using Structure from Motion Cues

This paper presents a complete solution for creating accurate 3D textured models from monocular video sequences. The methods are developed within the framework of sequential structure from motion, where a 3D model of the environment is maintained and updated as new visual information becomes available. The camera position is recovered by directly associating the 3D scene model with local image observations. Compared to standard structure from motion techniques, this approach decreases the error accumulation while increasing the robustness to scene occlusions and feature association failures. The obtained 3D information is used to generate high quality, composite visual maps of the scene (mosaics). The visual maps are used to create texture-mapped, realistic views of the scene

IEEE

Autor: Nicosevici, Tudor
García Campos, Rafael
Resum: This paper presents a complete solution for creating accurate 3D textured models from monocular video sequences. The methods are developed within the framework of sequential structure from motion, where a 3D model of the environment is maintained and updated as new visual information becomes available. The camera position is recovered by directly associating the 3D scene model with local image observations. Compared to standard structure from motion techniques, this approach decreases the error accumulation while increasing the robustness to scene occlusions and feature association failures. The obtained 3D information is used to generate high quality, composite visual maps of the scene (mosaics). The visual maps are used to create texture-mapped, realistic views of the scene
Accés al document: http://hdl.handle.net/2072/58666
Llenguatge: eng
Editor: IEEE
Drets: Tots els drets reservats
Matèria: Imatges -- Processament
Visió per ordinador
Visualització tridimensional (Informàtica)
Computer graphics
Image processing
Three-dimensional display systems
Títol: Online Robust 3D Mapping Using Structure from Motion Cues
Tipus: info:eu-repo/semantics/article
Repositori: Recercat

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