DocumentCode
2444340
Title
B-SIFT: A Binary SIFT Based Local Image Feature Descriptor
Author
Ni Zhen-Sheng
Author_Institution
State-Province Joint Lab. of Digital Home Interactive Applic., Sun Yat-sen Univ., Guangzhou, China
fYear
2012
fDate
23-25 Nov. 2012
Firstpage
117
Lastpage
121
Abstract
Local feature point detection and description are the basis for Computer Vision. SIFT is one of the most efficient local image descriptors and have been well studied in recent years. In this paper, we introduce B-SIFT, a novel binary local image descriptor which is based with SIFT. The method is compared with SIFT, and is shown that B-SIFT is better both in accuracy and efficiency.
Keywords
computer vision; feature extraction; object detection; transforms; B-SIFT; binary SIFT based local image feature descriptor; computer vision; image recognition; image registration; local feature point detection; scale invariant feature transform; visual tracking; Accuracy; Computer vision; Feature extraction; Histograms; Image retrieval; Vectors; Visualization; SIFT descriptor; binary image descriptor; image matching;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Home (ICDH), 2012 Fourth International Conference on
Conference_Location
Guangzhou
Print_ISBN
978-1-4673-1348-3
Type
conf
DOI
10.1109/ICDH.2012.69
Filename
6376395
Link To Document