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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Book ChapterDOI
Real-Time methods for long-term tissue feature tracking in endoscopic scenes
TL;DR: A novel framework to enable long-term tracking of image features is developed and two fast and robust feature algorithms are implemented, STAR and BRIEF, for application to endoscopic images that are able to acquire dense sets of salient features at real-time speeds.
Local Features in Image and Video Processing - Object Class Matching and Video Shot Detection
TL;DR: The local features are presented as a powerful tool in many applications and the imminent future work should concentrate on improving the quality of the local features.
DissertationDOI
Applying information theory to efficient SLAM
TL;DR: Focusing on the most challenging processes in a state of the art system, the Informati on Theoretic framework is applied to local motion estimation and maintenance of large probabi listic maps and gives rise to dynamic algorithms for quality map-par titioning and robust feature matching in the presence of significant ambiguity and va riable camera dynamics.
Journal ArticleDOI
FPGA-based module for SURF extraction
TL;DR: A complete hardware and software solution of an FPGA-based computer vision embedded module capable of carrying out SURF image features extraction algorithm, which allows to use the SURF algorithm in applications with power and spatial constraints, such as autonomous navigation of small mobile robots.
Patent
Method for image processing and an apparatus
TL;DR: In this article, a method in which one or more local descriptors relating to an interest point of an image are received is described, and a global descriptor is determined for the image on the basis of the local descriptor; and the global descriptors are compressed.
References
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Journal ArticleDOI
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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.