Keypoint Detection Based on Curvature Grouping and Adaptive Sampling
In the keypoint detection algorithm, the farthest point sampling methods and random sampling methods are usually used to select candidate points, then keypoints are screened out from the neighborhood of the candidate points. In the methods, reproducibility and interpretability of keypoints are relat...
Saved in:
| Main Authors: | Bifu Li, Yu Cheng, Weitong Li |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10623631/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Adaptive Focal Loss for Keypoint-Based Deep Learning Detectors Addressing Class Imbalance
by: Zhihao Su, et al.
Published: (2025-01-01) -
Detection and localization of copy-move tampering along with adversarial attack in a digital image
by: Anjali Diwan, et al.
Published: (2025-07-01) -
A detection method for synchronous recognition of string tomatoes and picking points based on keypoint detection
by: Linqiang Deng, et al.
Published: (2025-07-01) -
Adaptive Granularity-Fused Keypoint Detection for 6D Pose Estimation of Space Targets
by: Xu Gu, et al.
Published: (2024-11-01) -
Comparative Analysis of Keypoint Detection Performance in SIFT Implementations on Small-Scale Image Datasets
by: Arif Rahman, et al.
Published: (2024-12-01)