Intensity comparison based compact descriptor for mobile visual search

Author

Sang-il Na ; Keun-dong Lee ; Seung-Jae Lee ; Sung-kwan Je ; Weon-Geun Oh

Author_Institution

Creative Content Res. Lab., ETRI, Daejeon, South Korea

fYear

2013

Firstpage

103

Lastpage

106

Abstract

In this paper, we proposed intensity comparison based compact descriptor for mobile visual search. For practical mobile applications, the low complexity and the descriptor size are more preferable, and many algorithms such as SURF, CHoG, and PCA-SIFT have been proposed. However, these approaches focused on not the feature description but the extraction time and the size of the feature. This paper suggests feature description method based on simple intensity comparison with considering descriptor size and extraction speed. Experimental results show that the proposed method has comparable performance to SURF with similar complexity and 20 times much smaller size.

Keywords

computational complexity; feature extraction; information retrieval; mobile computing; transforms; CHoG algorithm; PCA-SIFT algorithm; SURF algorithm; descriptor size; feature description method; feature extraction speed; feature extraction time; feature size; intensity comparison-based compact descriptor; mobile applications; mobile visual search; scale invariant feature transform; Computer vision; Conferences; Equations; Feature extraction; Mobile communication; Pattern recognition; Visualization; feature descriptor; image matching;

fLanguage

English

Publisher

ieee

Conference_Titel

Frontiers of Computer Vision, (FCV), 2013 19th Korea-Japan Joint Workshop on

Conference_Location

Incheon

Print_ISBN

978-1-4673-5620-6

Type

conf

DOI

10.1109/FCV.2013.6485469

Filename

6485469