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- 저자 : Yuehong Shen (검색결과 5 건)
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A Noisy-Robust Approach for Facial Expression Recognition
( Ying Tong ),( Yuehong Shen ),( Bin Gao ),( Fenggang Sun ),( Rui Chen ),( Yefeng Xu ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.4
Accurate facial expression recognition (FER) requires reliable signal filtering and the effective feature extraction. Considering these requirements, this paper presents a novel approach for FER which is robust to noise. The main contributions of this work are: First, to preserve texture details in facial expression images and remove image noise, we improved the anisotropic diffusion filter by adjusting the diffusion coefficient according to two factors, namely, the gray value difference between the object and the background and the gradient magnitude of object. The improved filter can effectively distinguish facial muscle deformation and facial noise in face images. Second, to further improve robustness, we propose a new feature descriptor based on a combination of the Histogram of Oriented Gradients with the Canny operator (Canny-HOG) which can represent the precise deformation of eyes, eyebrows and lips for FER. Third, Canny-HOG`s block and cell sizes are adjusted to reduce feature dimensionality and make the classifier less prone to overfitting. Our method was tested on images from the JAFFE and CK databases. Experimental results in L-O-Sam-O and L-O-Sub-O modes demonstrated the effectiveness of the proposed method. Meanwhile, the recognition rate of this method is not significantly affected in the presence of Gaussian noise and salt-and-pepper noise conditions.
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A Novel and Efficient Wireless Communication System
Wei Zhao,Yuehong Shen,Zhigang Yuan,Yimin Wei,Wei Jian 보안공학연구지원센터 2015 International Journal of Future Generation Communi Vol.8 No.5
This paper aims to construct a novel wireless communication system, in which source signals are transmitted simultaneously in the same frequency band. The transmitted signals are only required to be statistically independent or statistically distinguished. Therefore, the source signals can be recovered at the receiver by utilizing the classical algorithms of blind source separation (BSS) and independent component analysis (ICA) such as the fast fixed-point algorithm (FastICA). On the one hand, because the source signals are transmitted simultaneously in the same frequency band, the spectrum efficiency of this novel system is much higher than those of time division multiplexing (TDM), frequency division multiplexing (FDM), and code division multiplexing (CDM) systems, in which TDM, FDM and CDM signals are limited in time interval, frequency band and code. On the other hand, inspired by recently proposed reference-based schemes, the reference signals are introduced to the classical separation algorithms of BSS and ICA, which makes this novel system much more efficient than classical ones in terms of computational speed. The performance of this new system is validated through realistic experiments. Additionally, it is theoretically shown that the information content of all the source signal inputs can be recovered by this novel wireless communication system.
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A New Ambiguity Elimination Method for BSS Block Signals in Time Domain
Wei Zhao,Fengshan Wang,Yuehong Shen,Yuanyuan Wu,Zhigang Yuan,Pengcheng Xu,Pengcheng Xu,Yimin Wei,Wei Jian 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.11
This paper deals with the ambiguity problem of blind source separation (BSS) in the case where continuously received mixture signals are split in time and processed block by block. Due to the inherent permutation and scaling ambiguities of BSS, tying the separated components at each adjacent time blocks doesn’t recover the original source signals correctly in general. Inspired by the Permutation Method of reconstructing source signal blocks in time domain, a new ambiguity elimination approach is proposed in this paper. This method aims to concatenate the separated components in adjacent blocks by artificially setting contrast blocks for each adjacent time blocks. The core idea of this method is to utilize the associativity between components recovered from contrast blocks and corresponding adjacent blocks. Compared with Permutation Method, the main advantage of this new method consists in the fact that it is much more efficient in terms of separation quality and computational speed. Besides, a tradeoff can be adjusted between separation quality and computational speed by choosing different length of contrast blocks. Real-life experiments are performed to validate the performance of this method on the wireless communication system with two transmitting and receiving antennas.
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RSNT-cFastICA for Complex-Valued Noncircular Signals in Wireless Sensor Networks
( Changliang Deng ),( Yimin Wei ),( Yuehong Shen ),( Wei Zhao ),( Hongjun Li ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.10
This paper presents an architecture for wireless sensor networks (WSNs) with blind source separation (BSS) applied to retrieve the received mixing signals of the sink nodes first. The little-to-no need of prior knowledge about the source signals of the sink nodes in the BSS method is obviously advantageous for WSNs. The optimization problem of the BSS of multiple independent source signals with complex and noncircular distributions from observed sensor nodes is considered and addressed. This paper applies Castella’s reference-based scheme to Novey’s negentropy-based algorithms, and then proposes a novel fast fixed-point (FastICA) algorithm, defined as the reference-signal negentropy complex FastICA (RSNT-cFastICA) for complex-valued noncircular-distribution source signals. The proposed method for the sink nodes is substantially more efficient than Novey’s quasi-Newton algorithm in terms of computational speed under large numbers of samples, can effectively improve the power consumption effeciency of the sink nodes, and is significantly beneficial for WSNs and wireless communication networks (WCNs). The effectiveness and performance of the proposed method are validated and compared with three related BSS algorithms through theoretical analysis and simulations.
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