Real-time Localization in Outdoor Environments using Stereo Vision and Inexpensive GPS

By Motilal Agrawal, Kurt Konolige. International Conference on Pattern Recognition, 2006

321 citations recorded by the source corpus.

How researchers see this paper

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A sensor fusion approach for localization with cumulative error elimination (2012, methodology): “Agrawal and Konolige [7] present a localization method using stereo vision and GPS.”
FrameSLAM: From Bundle Adjustment to Real-Time Visual Mapping (2008, methodology): “We show results both with and without IMU assistance.”
Accurate indoor localization with zero start-up cost (2014, background): “Object Geo-tagging: There has been much work in computer vision on stereo-imaging and 3D-reconstruction to localize objects relative to known camera locations or to find relative locations of different objects in the same scene [2, 29].”
Real-time stereo visual odometry for autonomous ground vehicles (2008, background): “That is, the combination of stereo ranging and stereo visual odometry is generally faster and more reliable than stereo ranging followed by monocular visual odometry.”
Large-Scale Visual Odometry for Rough Terrain (2007, methodology): “SfM systems are a type of feature-tracking method that use structure-from-motion methods to estimate the relativ position of two or more camera frames, based on matching features [1], [2], [4], [16], [18].”
Visual odometry based on stereo image sequences with RANSAC-based outlier rejection scheme (2010, methodology): “The information given by such images sufﬁces for precise motion estimation based on visual information [1], called visual odometry (e.g., Nist´er et. al.”