Book ChapterDOI
CenSurE: Center Surround Extremas for Realtime Feature Detection and Matching
Motilal Agrawal,Kurt Konolige,Morten Rufus Blas +2 more
- pp 102-115
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TLDR
A suite of scale-invariant center-surround detectors (CenSurE) that outperform the other detectors, yet have better computational characteristics than other scale-space detectors, and are capable of real-time implementation are introduced.Abstract:
We explore the suitability of different feature detectors for the task of image registration, and in particular for visual odometry, using two criteria: stability (persistence across viewpoint change) and accuracy (consistent localization across viewpoint change). In addition to the now-standard SIFT, SURF, FAST, and Harris detectors, we introduce a suite of scale-invariant center-surround detectors (CenSurE) that outperform the other detectors, yet have better computational characteristics than other scale-space detectors, and are capable of real-time implementation.read more
Citations
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Sistema de navegación monocular para robots móviles en ambientes interiores/exteriores
TL;DR: For example, ExaBot as discussed by the authors is based on two tecnicas of navegacion visual: one basada en segmentation of imagenes and another basada in marcas visuales.
Journal ArticleDOI
POP: A generic framework for real-time pose estimation of planar objects
TL;DR: POP is proposed, a generic real-time planar-object pose-estimation framework which is designed to handle the aforementioned types of errors while not losing generality to a specific choice of keypoint detection or tracking algorithm.
Journal ArticleDOI
Feature Extractors Evaluation Based V-SLAM for Autonomous Vehicles
TL;DR: The aim of this paper is to evaluate the possible combinations of detectors and descriptors to achieve a precise localization while considering the processing times with SLAM algorithms over well-known indoor and outdoor datasets.
Book ChapterDOI
Feature-Based Tracking via SURF Detector and BRISK Descriptor
Sangeen Khan,Sehat Ullah +1 more
TL;DR: In this article, the authors presented a markerless tracking system that tracks natural features of the object in real-time and is very economical in terms of computation, as it identifies highly repeatable interest points in the object and BRISK descriptor, due to its low computational cost and invariance to scale and rotation which is vital for every visual tracking system.
Posted Content
Features for Ground Texture Based Localization -- A Survey
TL;DR: In this paper, the first extensive evaluation of available feature extraction methods for ground texture based vehicle localization using feature-based methods is provided, using separately taken image pairs as well as synthetic transformations.
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.
Journal ArticleDOI
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
TL;DR: New results are derived on the minimum number of landmarks needed to obtain a solution, and algorithms are presented for computing these minimum-landmark solutions in closed form that provide the basis for an automatic system that can solve the Location Determination Problem under difficult viewing.
Proceedings ArticleDOI
A Combined Corner and Edge Detector
Chris Harris,Mike Stephens +1 more
TL;DR: The problem the authors are addressing in Alvey Project MMI149 is that of using computer vision to understand the unconstrained 3D world, in which the viewed scenes will in general contain too wide a diversity of objects for topdown recognition techniques to work.
Book ChapterDOI
SURF: speeded up robust features
TL;DR: A novel scale- and rotation-invariant interest point detector and descriptor, coined SURF (Speeded Up Robust Features), which approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can be computed and compared much faster.
Proceedings ArticleDOI
Robust real-time face detection
Paul A. Viola,Michael Jones +1 more
TL;DR: A new image representation called the “Integral Image” is introduced which allows the features used by the detector to be computed very quickly and a method for combining classifiers in a “cascade” which allows background regions of the image to be quickly discarded while spending more computation on promising face-like regions.