The vSLAM Algorithm for Robust Localization and Mapping

By Niklas Karlsson, Enrico Di Bernardo, J. Ostrowski, Luis Goncalves, Paolo Pirjanian, Mario E. Munich. Proceedings of the 2005 IEEE International Conference on Robotics and Automation, 2005

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MonoSLAM: Real-Time Single Camera SLAM (2007, methodology): “The commercial vSLAM system [36] also uses SIFT features, though within aSLAM algorithm which relies significantly on odometry to build a connected map of recognizable locations rather than fully continuous accurate localization.”
Mapping Large Loops with a Single Hand-Held Camera (2007, background): “Nevertheless, the combination of detailed 3D geometric and photometric information available from cameras means that they have great promise for SLAM applications of all types, and recent progress has been very encouraging.”
A reliable and accurate indoor localization method using phone inertial sensors (2012, background): “Because of the lack of reliable GPS signals inside a building, researchers have explored the use of WiFi beacons [2, 27], magnetometer [6], vision [10], or ultrasound [24], to name a few, for coarse level indoor positioning.”
Mapping a Suburb With a Single Camera Using a Biologically Inspired SLAM System (2008, methodology): “The size of the video is 22 MB in stlucia_wmv9.avi format and 35 MB in stlucia_mpeg4.avi format. stlucia_wmv9.avi is playable in Windows Media Player versions 9 and above. stlucia_mpeg4.avi uses the xvid MPEG4 codec (1.1.2 or later).”
Incremental smoothing and mapping (2008, methodology): “It is frequently used in SFM [6], visual SLAM [120, 21, 82] and visual odometry [110].”