NDLI: Robot robust object recognition based on fast SURF feature matching

Content Provider	IEEE Xplore Digital Library
Author	Mingfang Du Junzheng Wang Jing Li Haiqing Cao Guangtao Cui Jianjun Fang Ji Lv Xusheng Chen
Copyright Year	2013
Description	Author affiliation: Autom. Sch., Beijing Union Univ., Beijing, China (Jianjun Fang; Ji Lv; Xusheng Chen) \|\| Key Lab. of Complex Syst. Intell. Control & Decision, Beijing Inst. of Technol., Beijing, China (Mingfang Du; Junzheng Wang; Jing Li; Haiqing Cao; Guangtao Cui)
Abstract	The local invariant features SURF (Speeded Up Robust Features) is introduced into the robot visual recognition field to solve scale changes, rotation, perspective changes, changes in illumination and other problems. A Speeded up SURF (SSURF) algorithm is proposed to meet the needs of robot visual identification. In SSURF algorithms, the main direction determination step of SURF algorithm is modified which make the search scope of the main direction becomes {-α, +α} (0 ≤ α ≤ 30°) from the original scope 360 According to compressed sensing ideas and interest points distribution histogram, the main scale search space is selected to improve the interest points searching step of SURF algorithm, so the interest points searching time-consuming is reduced. Matching the sample object and the scene using SSURF descriptor, and positioning the target position in the scene and giving ROI(region of interest). Experimental results in the autonomous mobile robot platform show that the proposed method significantly improves the speed of the robot to identify the target object, and proved robust to the scale changes, rotation, perspective changes, changes in illumination.
Sponsorship	IEEE Syst., Man, Cybern. Soc.
Starting Page	581
Ending Page	586
File Size	859702
Page Count	6
File Format	PDF
e-ISBN	9781479903337
DOI	10.1109/CAC.2013.6775802
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-07
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Visualization SURF Image recognition Local invariant features Feature extraction Feature matching Robustness Vectors Object recognition Robots
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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