Shi–Tomasi corner detector
E989632
UNEXPLORED
The Shi–Tomasi corner detector is a computer vision algorithm that identifies good feature points (corners) in images for robust tracking and recognition tasks.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Shi–Tomasi corner detector canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T12573054 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shi–Tomasi corner detector Context triple: [Kanade–Lucas–Tomasi feature tracker, relatedTo, Shi–Tomasi corner detector]
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A.
Kanade–Lucas–Tomasi feature tracker
The Kanade–Lucas–Tomasi feature tracker is a widely used computer vision algorithm for robustly tracking distinctive image features across video frames, building on the Lucas–Kanade optical flow method with Tomasi’s feature selection criteria.
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B.
Lucas–Kanade optical flow algorithm
The Lucas–Kanade optical flow algorithm is a widely used computer vision method for estimating the motion of features between consecutive images by assuming locally constant motion and solving a least-squares problem.
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C.
European Conference on Computer Vision
The European Conference on Computer Vision (ECCV) is a leading biennial research conference that showcases cutting-edge advances in computer vision and pattern recognition.
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D.
ILD detector concept
The ILD detector concept is a proposed high-precision particle physics detector design for the International Linear Collider, optimized for detailed reconstruction of complex collision events.
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E.
ANSAC
ANSAC is the abbreviation for the Applied and Natural Science Accreditation Commission, a body that accredits applied and natural science degree programs.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shi–Tomasi corner detector Target entity description: The Shi–Tomasi corner detector is a computer vision algorithm that identifies good feature points (corners) in images for robust tracking and recognition tasks.
-
A.
Kanade–Lucas–Tomasi feature tracker
The Kanade–Lucas–Tomasi feature tracker is a widely used computer vision algorithm for robustly tracking distinctive image features across video frames, building on the Lucas–Kanade optical flow method with Tomasi’s feature selection criteria.
-
B.
Lucas–Kanade optical flow algorithm
The Lucas–Kanade optical flow algorithm is a widely used computer vision method for estimating the motion of features between consecutive images by assuming locally constant motion and solving a least-squares problem.
-
C.
European Conference on Computer Vision
The European Conference on Computer Vision (ECCV) is a leading biennial research conference that showcases cutting-edge advances in computer vision and pattern recognition.
-
D.
ILD detector concept
The ILD detector concept is a proposed high-precision particle physics detector design for the International Linear Collider, optimized for detailed reconstruction of complex collision events.
-
E.
ANSAC
ANSAC is the abbreviation for the Applied and Natural Science Accreditation Commission, a body that accredits applied and natural science degree programs.
- F. None of above. chosen
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.