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- 저자 : ( Yutian Chen ) (검색결과 2 건)
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Efficient Visual Place Recognition by Adaptive CNN Landmark Matching
( Yutian Chen ),( Wenyan Gan ),( Yi Zhu ),( Hui Tian ),( Cong Wang ),( Wenfeng Ma ),( Yunbo Li ),( Dong Wang ),( Jixian He ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.11
Visual place recognition (VPR) is a fundamental yet challenging task of mobile robot navigation and localization. The existing VPR methods are usually based on some pairwise similarity of image descriptors, so they are sensitive to visual appearance change and also computationally expensive. This paper proposes a simple yet effective four-step method that achieves adaptive convolutional neural network (CNN) landmark matching for VPR. First, based on the features extracted from existing CNN models, the regions with higher significance scores are selected as landmarks. Then, according to the coordinate positions of potential landmarks, landmark matching is improved by removing mismatched landmark pairs. Finally, considering the significance scores obtained in the first step, robust image retrieval is performed based on adaptive landmark matching, and it gives more weight to the landmark matching pairs with higher significance scores. To verify the efficiency and robustness of the proposed method, evaluations are conducted on standard benchmark datasets. The experimental results indicate that the proposed method reduces the feature representation space of place images by more than 75% with negligible loss in recognition precision. Also, it achieves a fast matching speed in similarity calculation, satisfying the real-time requirement.
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Pengfei Cheng,Yutian Wang,Zhikun Chen,Zhe Yang 한국광학회 2016 Current Optics and Photonics Vol.20 No.1
Oil pollution seriously endangers the biological environment and human health. Due to the diversityof oils and the complexity of oil composition, it is of great significance to identify the oil contaminants. The 3-D fluorescence spectrum combined with a second order correction algorithm was adopted to measurean oil mixture with overlapped fluorescence spectra. The self-weighted alternating trilinear decomposition(SWATLD) is a kind of second order correction, which has developed rapidly in recent years. Micellarsolutions of #0 diesel, #93 gasoline and ordinary kerosene in different concentrations were made up. The3-D fluorescence spectra of the mixed oil solutions were measured by a FLS920 fluorescence spectrometer. The SWATLD algorithm was applied to decompose the spectrum data. The predict concentration andrecovery rate obtained by the experiment show that the SWATLD algorithm has advantages of insensitivityto component number and high resolution for mixed oils.
ScienceON
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