Journal ArticleDOI
Visual-inertial navigation, mapping and localization: A scalable real-time causal approach
Eagle Jones,Stefano Soatto +1 more
TLDR
An integrated approach to ‘loop-closure’, that is the recognition of previously seen locations and the topological re-adjustment of the traveled path, is described, where loop-closure can be performed without the need to re-compute past trajectories or perform bundle adjustment.Citations
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Journal ArticleDOI
Keyframe-based visual-inertial odometry using nonlinear optimization
TL;DR: This work forms a rigorously probabilistic cost function that combines reprojection errors of landmarks and inertial terms and compares the performance to an implementation of a state-of-the-art stochastic cloning sliding-window filter.
Journal ArticleDOI
Visual Odometry [Tutorial]
TL;DR: Visual odometry is the process of estimating the egomotion of an agent (e.g., vehicle, human, and robot) using only the input of a single or If multiple cameras attached to it, and application domains include robotics, wearable computing, augmented reality, and automotive.
Journal ArticleDOI
Visual simultaneous localization and mapping: a survey
TL;DR: A brief and comprehensible review of the state-of-the-art computer vision techniques employed in visual SLAM, such as detection, description and matching of salient features, image recognition and retrieval, among others, are provided.
Journal ArticleDOI
High-precision, consistent EKF-based visual-inertial odometry
TL;DR: A novel, real-time EKF-based VIO algorithm is proposed, which achieves consistent estimation by ensuring the correct observability properties of its linearized system model, and performing online estimation of the camera-to-inertial measurement unit (IMU) calibration parameters.
Proceedings ArticleDOI
Robust visual inertial odometry using a direct EKF-based approach
TL;DR: A monocular visual-inertial odometry algorithm which achieves accurate tracking performance while exhibiting a very high level of robustness by directly using pixel intensity errors of image patches, leading to a truly power-up-and-go state estimation system.
References
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Journal ArticleDOI
Distinctive Image Features from Scale-Invariant Keypoints
TL;DR: This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.
Proceedings ArticleDOI
Histograms of oriented gradients for human detection
Navneet Dalal,Bill Triggs +1 more
TL;DR: It is shown experimentally that grids of histograms of oriented gradient (HOG) descriptors significantly outperform existing feature sets for human detection, and the influence of each stage of the computation on performance is studied.
Proceedings Article
An iterative image registration technique with an application to stereo vision
Bruce D. Lucas,Takeo Kanade +1 more
TL;DR: In this paper, the spatial intensity gradient of the images is used to find a good match using a type of Newton-Raphson iteration, which can be generalized to handle rotation, scaling and shearing.
Journal ArticleDOI
Term Weighting Approaches in Automatic Text Retrieval
Gerard Salton,Chris Buckley +1 more
TL;DR: This paper summarizes the insights gained in automatic term weighting, and provides baseline single term indexing models with which other more elaborate content analysis procedures can be compared.
Proceedings ArticleDOI
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
TL;DR: This paper presents a method for recognizing scene categories based on approximate global geometric correspondence that exceeds the state of the art on the Caltech-101 database and achieves high accuracy on a large database of fifteen natural scene categories.