상세정보
학술지
Keypoint Detection Using Higher Order Laplacian of Gaussian
- 발행일
- 202001
- 출처
- IEEE Access, v.8, pp.10416-10425
- ISSN
- 2169-3536
- 출판사
- IEEE
- 협약과제
- 19ZR1100, 초실감 공간미디어 원천기술 개발, 서정일
- 초록
- This paper presents a keypoint detection method based on the Laplacian of Gaussian (LoG). In contrast to the Difference of Gaussian (DoG)-based keypoint detection method used in Scale Invariant Feature Transform (SIFT), we focus on the LoG operator and its higher order derivatives. We provide mathematical analogies between higher order DoG (HDoG) and higher order LoG (HLoG) and experimental results to show the effectiveness of the proposed HLoG-based keypoint detection method. The performance of the HLoG is evaluated with four different tests: i) a repeatability test of the keypoints detected across images under various transformations, ii) image retrieval, iii) panorama stitching and iv) 3D reconstruction. The proposed HLoG method provides comparable performance to HDoG and the combination of HLoG and HDoG provides significant improvements in various keypoint-related computer vision problems.
- KSP 제안 키워드
- 3D Reconstruction, Computer Vision(CV), Detection Method, Difference of Gaussian(DoG), Higher order, Image retrieval, Keypoint Detection, LoG operator, laplacian of Gaussian, panorama stitching, scale invariant feature transform(SIFT)