DocumentCode
186779
Title
Fast image retrieval with grid-based keypoint detector and binary descriptor
Author
SuGil Choi ; Seungwan Han
Author_Institution
Software Contents Res. Lab., Electron. & Telecommun. Res. Inst., Daejeon, South Korea
fYear
2014
fDate
22-24 Oct. 2014
Firstpage
679
Lastpage
680
Abstract
As an alternative to vector-based descriptors, such as SIFT and SURF, more computationally efficient binary descriptors, such as BRISK and ORB, have recently been proposed. These binary descriptors are usually used in combination with a novel scale-space FAST-based detector to be suitable for real-time applications, but it consumes more time than creating binary descriptors. Therefore, if accuracy can be kept similar, keypoint sampling by a grid is better than FAST-based detector because it consumes almost no time. In this paper, grid-based sampling and BRISK keypoint detector are tested for image retrieval. Experimental results demonstrate that grid-based sampling out performs keypoint detector in terms of accuracy and processing speed.
Keywords
image retrieval; sampling methods; BRISK keypoint detector; ORB; SIFT; SURF; binary descriptor; grid-based keypoint detector; grid-based sampling; image retrieval; keypoint sampling; scale-space FAST-based detector; vector-based descriptor; Accuracy; Computational efficiency; Computer vision; Detectors; Image retrieval; Real-time systems; Visualization; binary descriptor; grid-based sampling; image retrieval;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Communication Technology Convergence (ICTC), 2014 International Conference on
Conference_Location
Busan
Type
conf
DOI
10.1109/ICTC.2014.6983253
Filename
6983253
Link To Document