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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Transition: A Relevant Image Feature for Fast Obstacle Detection
TL;DR: A novel fast feature-point extractor applied along a 1D signal is proposed that is 100 times faster than Harris and relevant on man-made objects and can be used to detect various types of obstacles with an 80MHz CPU.
Journal ArticleDOI
A Comparative Analysis of Pattern Matching Techniques Towards OGM Evaluation
TL;DR: An overview of the existing automatic alignment techniques of two occupancy grid maps that employ pattern matching is provided, as well as a method to eliminate erroneous correspondences, aiming at producing the correct transformation between the two maps.
Proceedings ArticleDOI
Nestle: Interest point extraction via nested circles
Erhan Gundogdu,A. Aydin Alatan +1 more
TL;DR: The performance tests on the repeatability of these keypoints signify the promising performance of the proposed algorithm to be used in many resource limited computer vision applications due to its efficiency and competitive repeatability performance.
Journal ArticleDOI
Strip wrinkling detection based on feature extraction and sparse representation
Wenhao Wang,Xiong Chen,Yuqi Pan +2 more
TL;DR: A feature-based image processing method for strip wrinkling detection, which has been tested in a strip steel production line and the performance showed its applicability.
Proceedings ArticleDOI
Lisbon Landmark Lenslet Light Field Dataset: Description and Retrieval Performance
TL;DR: This paper proposes and assesses straightforward extensions of visual 2D descriptor matching for lenslet light field retrieval and shows that gains up to 14% can be obtained with a light field representation when compared to a 2D imaging conventional representation.
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.