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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Journal ArticleDOI
A Light Visual Mapping and Navigation Framework for Low-Cost Robots
TL;DR: A novel light and robust topometric simultaneous localization and mapping framework using appearance-based visual loop-closure detection enhanced with the odometry, which is particularly well suited for low-power robots as it is not dependent on the image processing frequency and latency, and thus it can be applied using remote processing.
Journal Article
Enhancement of SURF performance through masked grey world approach
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Implementation of an Open Source Based Augmented Reality Engine for Cloud Authoring Frameworks
TL;DR: A pipeline model and sample implementation is presented that shows how an Augmented Reality engine can be built by leveraging advances in open source algorithm implementations and can be effectively integrated with cloud authoring tools to take advantage of the network connectivity and its computing power.
Proceedings ArticleDOI
Evaluation of point matching methods for wide-baseline stereo correspondence on mobile platforms
TL;DR: This work provides quantitative comparison of the most important keypoint detectors and descriptors in the context of wide baseline stereo matching and finds that for resolution of 2 megapixels images the current mobile hardware is capable of providing results efficiently.
Journal ArticleDOI
PIMR: Parallel and Integrated Matching for Raw Data
TL;DR: This work brings forward a fast and robust matching algorithm, named parallel and integrated matching for raw data (PIMR), which not only effectively utilizes the color information of raw data, but also designs a Parallel and integrated framework to shorten the time-cost in the demosaicing stage.
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.