DocumentCode :
2379489
Title :
Efficient visual salient object landmark extraction and recognition
Author :
Lee, Lae-Kyoung ; An, Su-Yong ; Oh, Se-young
Author_Institution :
Dept. of Electr. & Electron. Eng., Pohang Univ. of Sci. & Technol. (POSTECH), Pohang, South Korea
fYear :
2011
fDate :
9-12 Oct. 2011
Firstpage :
1351
Lastpage :
1357
Abstract :
This article presents an efficient visual landmark extraction and recognition method that can autonomously and rapidly detect visual features such as objects or groups of small objects, and that can be applied to visual object recognition based SLAM and navigation in indoor/large environments using a monocular/omnidirection vision system. Our method consists of two-stage: (1) we autonomously extract object regions with modified fuzzy object segmentation. We generate a saliency map of the scene based on Modified Phase spectrum of Fourier Transform (mPFT) and extract the final salient object landmark with weighted combination of candidate of objects and saliency map. (2) Using these result, we register current objects as visual landmark and then recognize the current image the scale invariant feature transform (SIFT) - based recognition with probabilistic voting. In experiments results in real indoor and large hall environments, the proposed method was simpler and 10~15% better performance in computation efficiency and successfully extracted salient object landmark in complex environments with high recognition rates. The proposed algorithm can be easily implemented in real-time by reducing the number of objects considered.
Keywords :
SLAM (robots); image segmentation; navigation; object recognition; Fourier transform; SLAM; indoor environment; modified fuzzy object segmentation; modified phase spectrum; monocular/omnidirection vision system; navigation; probabilistic voting; scale invariant feature transform; scene saliency map; visual features; visual salient object landmark extraction; visual salient object landmark recognition; Feature extraction; Image segmentation; Merging; Navigation; Object segmentation; Simultaneous localization and mapping; Visualization; Fuzzy object segmentation; SIFT; SLAM; Saliency map; Visual landmark;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2011 IEEE International Conference on
Conference_Location :
Anchorage, AK
ISSN :
1062-922X
Print_ISBN :
978-1-4577-0652-3
Type :
conf
DOI :
10.1109/ICSMC.2011.6083846
Filename :
6083846
Link To Document :
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