Search results for " feature matching"

showing 2 items of 2 documents

Accurate keyframe selection and keypoint tracking for robust visual odometry

2016

This paper presents a novel stereo visual odometry (VO) framework based on structure from motion, where a robust keypoint tracking and matching is combined with an effective keyframe selection strategy. In order to track and find correct feature correspondences a robust loop chain matching scheme on two consecutive stereo pairs is introduced. Keyframe selection is based on the proportion of features with high temporal disparity. This criterion relies on the observation that the error in the pose estimation propagates from the uncertainty of 3D points—higher for distant points, that have low 2D motion. Comparative results based on three VO datasets show that the proposed solution is remarkab…

0209 industrial biotechnologyMatching (graph theory)Computer scienceVisual odometryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyKeyframe selectionRANSAC020901 industrial engineering & automation0202 electrical engineering electronic engineering information engineeringStructure from motionComputer visionVisual odometryVisual Odometry Structure from Motion RANSAC feature matching keyframe selectionPoseSelection (genetic algorithm)Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniRANSACSettore INF/01 - InformaticaFeature matchingbusiness.industryStructure from motionPattern recognitionComputer Science ApplicationsHardware and ArchitectureFeature (computer vision)Pattern recognition (psychology)020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligencebusinessSoftware
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New Error Measures to Evaluate Features on Three-Dimensional Scenes

2011

In this paper new error measures to evaluate image features in three-dimensional scenes are proposed and reviewed. The proposed error measures are designed to take into account feature shapes, and ground truth data can be easily estimated. As other approaches, they are not error-free and a quantitative evaluation is given according to the number of wrong matches and mismatches in order to assess their validity

Ground truthFeature Detector Feature Descriptor Overlap Error Epipolar Geometry Feature Matching and ComparisonSettore INF/01 - InformaticaFeature (computer vision)business.industryEpipolar geometryFeature descriptorPattern recognitionArtificial intelligencebusinessFeature matchingMathematics
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