Performance evaluation of feature detection and feature matching for stereo visual odometry using SIFT and SURF

Author

Suaib, Norhayati Mohd ; Marhaban, Mohammad Hamiruce ; Saripan, M. Iqbal ; Ahmad, Siti Anom

Author_Institution

Dept. of Electr. & Electron. Eng., Univ. Putra Malaysia, Serdang, Malaysia

fYear

2014

fDate

14-16 April 2014

Firstpage

200

Lastpage

203

Abstract

Feature detection and feature matching are the most crucial parts in visual odometry process. In order to suit the real time process in visual odometry, both of the stages must be robust but at the same time are fast to compute. This paper presents the evaluation of Scale Invariant Feature Transform (SIFT) and Speeded Up Robust Feature (SURF) performances. The results show that SURF is outperform than SIFT in term of rate of matched points and also in computational time.

Keywords

distance measurement; feature extraction; image matching; stereo image processing; transforms; SIFT; SURF; feature detection; feature matching; performance evaluation; real time process; scale invariant feature transform; speeded up robust feature performances; stereo visual odometry process; Cameras; Detectors; Feature extraction; Performance evaluation; Robots; Robustness; Visualization; SIFT; SURF; feature detection; feature matching; visual odometry;

fLanguage

English

Publisher

ieee

Conference_Titel

Region 10 Symposium, 2014 IEEE

Conference_Location

Kuala Lumpur

Print_ISBN

978-1-4799-2028-0

Type

conf

DOI

10.1109/TENCONSpring.2014.6863025

Filename

6863025