• Title/Summary/Keyword: Mean vector

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3D Human Face Segmentation using Curvature Estimation (Curvature Estimation을 이용한 3차원 사람얼굴 세그멘테이션)

  • Seongdong Kim;Seonga Chin;Moonwon Choo
    • Journal of Korea Multimedia Society
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    • v.6 no.6
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    • pp.985-990
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    • 2003
  • This paper presents the representation and its shape analysis of face by features based on surface curvature estimation and proposed rotation vector of the human face. Curvature-based surface features are well suited to use for experimenting the 3D human face segmentation. Human surfaces are exactly extracted and computed with parameters and rotated by using active surface mesh model. The estimated features were tested and segmented by reconstructing surfaces from the face surface and analytically computing Gaussian (K) and mean (H) curvatures without threshold.

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CONTRACTION OF HOROSPHERE-CONVEX HYPERSURFACES BY POWERS OF THE MEAN CURVATURE IN THE HYPERBOLIC SPACE

  • Guo, Shunzi;Li, Guanghan;Wu, Chuanxi
    • Journal of the Korean Mathematical Society
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    • v.50 no.6
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    • pp.1311-1332
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    • 2013
  • This paper concerns the evolution of a closed hypersurface of the hyperbolic space, convex by horospheres, in direction of its inner unit normal vector, where the speed equals a positive power ${\beta}$ of the positive mean curvature. It is shown that the flow exists on a finite maximal interval, convexity by horospheres is preserved and the hypersurfaces shrink down to a single point as the final time is approached.

SIFT-based Stereo Matching to Compensate Occluded Regions and Remove False Matching for 3D Reconstruction

  • Shin, Do-Kyung;Lee, Jeong-Ho;Moon, Young-Shik
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.418-422
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    • 2009
  • Generally, algorithms for generating disparity maps can be clssified into two categories: region-based method and feature-based method. The main focus of this research is to generate a disparity map with an accuracy depth information for 3-dimensional reconstructing. Basically, the region-based method and the feature-based method are simultaneously included in the proposed algorithm, so that the existing problems including false matching and occlusion can be effectively solved. As a region-based method, regions of false matching are extracted by the proposed MMAD(Modified Mean of Absolute Differences) algorithm which is a modification of the existing MAD(Mean of Absolute Differences) algorithm. As a feature-based method, the proposed method eliminates false matching errors by calculating the vector with SIFT and compensates the occluded regions by using a pair of adjacent SIFT matching points, so that the errors are reduced and the disparity map becomes more accurate.

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Measurement of vertical migration speed of Sound Scattering Layer using an bottom mooring type Acoustic Doppler Current Profiler (해저설치형 음향도플러유향유속계를 이용한 음향산란층의 연직이동속도 측정)

  • Jo, Hyeon-Jeong;Lee, Kyoung-Hoon
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.46 no.4
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    • pp.449-457
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    • 2010
  • This study shows that the vertical migration speed of sound scattering layers (SSLs), which is distributed in near Funka Bay, were measured by 3D velocity components acquired from a bottom moorng ADCP. While the bottom mooring type has a problem to measure the velocity vectors of sound scattering layer distributed near to surface, both the continuous vertical migration patterns and variability of backscatterers were routinely investigated as well. In addition, the velocity vectors were compared with the vertical migration velocity estimated from echograms of Mean Volume Backscattering Strength, and estimated to produce observational bias due to SSLs which is composed of backscatterers such as euphausiids, nekton, and fishes have swimming ability.

Development and Application of Measuring Method for Instantaneous Intensity (순시 인텐시티 측정 기법의 개발 및 응용)

  • 이장우;안병하
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.05a
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    • pp.960-963
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    • 2003
  • Sound intensity method is well known as a visualization technique of sound field and sound propagation in noise control. Sound intensity is a vector quantity that describes the magnitude and the direction of net flow of acoustic energy at a given position. The current measuring method is expensive and difficult to identify the noise source exactly. In this paper, we have studied the noise source identification and the characteristics of noise source of rotary compressor for air conditioner using complex sound intensity method. The new method for instantaneous sound intensity is also proposed and it is useful for transient state and steady state. The criteria of these state, select auto correlation coefficient. The advantage, simplicity and economic attribution of this method are verified by analyzing the characteristics of noise source with instantaneous sound intensity compared to mean sound intensity.

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Numerical Simulation of Thermal Fluctuation of Hot and Cold Fluids Mixing in a Tee Junction

  • Gao, Kai;Lu, Tao
    • International Journal of Advanced Culture Technology
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    • v.3 no.2
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    • pp.171-178
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    • 2015
  • In this work, mixing processes of hot and cold fluids of three different jet types are predicted by large-eddy simulation (LES) on FLUENT platform. Temperature at different positions of internal wall and mixing conditions of T-junctions at different times are obtained, then the simulated normalized mean and root-mean square (RMS) temperature, temperature contour and velocity vector of every case are compared. The results indicate that, the mixing regions in the tee junction is related to the jet type, and temperature fluctuations on the pipe wall in the type of the deflecting jet is the least.

Noise Robust Speech Recognition Based on Noisy Speech Acoustic Model Adaptation (잡음음성 음향모델 적응에 기반한 잡음에 강인한 음성인식)

  • Chung, Yongjoo
    • Phonetics and Speech Sciences
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    • v.6 no.2
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    • pp.29-34
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    • 2014
  • In the Vector Taylor Series (VTS)-based noisy speech recognition methods, Hidden Markov Models (HMM) are usually trained with clean speech. However, better performance is expected by training the HMM with noisy speech. In a previous study, we could find that Minimum Mean Square Error (MMSE) estimation of the training noisy speech in the log-spectrum domain produce improved recognition results, but since the proposed algorithm was done in the log-spectrum domain, it could not be used for the HMM adaptation. In this paper, we modify the previous algorithm to derive a novel mathematical relation between test and training noisy speech in the cepstrum domain and the mean and covariance of the Multi-condition TRaining (MTR) trained noisy speech HMM are adapted. In the noisy speech recognition experiments on the Aurora 2 database, the proposed method produced 10.6% of relative improvement in Word Error Rates (WERs) over the MTR method while the previous MMSE estimation of the training noisy speech produced 4.3% of relative improvement, which shows the superiority of the proposed method.

Designing Statistical Test for Mean of Random Profiles

  • Bahri, Mehrab;Hadi-Vencheh, Abdollah
    • Industrial Engineering and Management Systems
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    • v.15 no.4
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    • pp.432-445
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    • 2016
  • A random profile is the result of a process, the output of which is a function instead of a scalar or vector quantity. In the nature of these objects, two main dimensions of "functionality" and "randomness" can be recognized. Valuable researches have been conducted to present control charts for monitoring such processes in which a regression approach has been applied by focusing on "randomness" of profiles. Performing other statistical techniques such as hypothesis testing for different parameters, comparing parameters of two populations, ANOVA, DOE, etc. has been postponed thus far, because the "functional" nature of profiles is ignored. In this paper, first, some needed theorems are proven with an applied approach, so that be understandable for an engineer which is unfamiliar with advanced mathematical analysis. Then, as an application of that, a statistical test is designed for mean of continuous random profiles. Finally, using experimental operating characteristic curves obtained in computer simulation, it is demonstrated that the presented tests are properly able to recognize deviations in the null hypothesis.

A New Hybrid Coder for High Quality Image Compression

  • Lee, Hang-Chan
    • Journal of Electrical Engineering and information Science
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    • v.2 no.6
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    • pp.36-42
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    • 1997
  • This paper presents a new design technique for performing high quality low bit rate image compression. A hybrid coder(HC) which combines Mean Removed Important Coefficient Selection based JPEG(MR-ICS-JPEG) and Adaptive Vector Quantization (AVQ) is proposed. A new quantization table is developed using the Important Coefficient Selection(ICS) method; the importance of each coefficient is determined using the orthonormal property of the DCT. This quantization table is applied to standard JPEG with mean removal(MR) strategy before processing. This scheme, called MR-ICS-JPEG, produces more than 2 dB enhanced performance in terms of PSNR over standard JPEG. A set of homogeneous codebooks is generated by homogeneous training vectors. Before compression, an image is uniformly divided into 8${\times}$8 blocks. Low detail regions such as backgrounds are roughly coded by AVQ while high detail regions such as edges or curves are finely coded by the proposed MR-ICS-JPEG. This hybrid coder procuces consistently about 3 dB improved performance in terms of PSNR over standard JPEG.

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The Short Time Spectra Analysis System Using The Complex LMS Algorithm and It's Applications

  • Umemoto, Toshitaka;Fujisawa, Shoichiro;Yoshida, Takeo
    • 제어로봇시스템학회:학술대회논문집
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    • 1998.10a
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    • pp.58-63
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    • 1998
  • B.Widrow established fundamental relations between the least-mean-square (LMS) algorithm and the digital Fourier transform[1]. By extending these relations, we proposed the short time spectra analysis system using the LMS algorithm[2]. In that paper, we used the normal LMS algorithm on the thought of dealing with only real analytical signal. This algorithm minimizes the real mean-square by recursively altering the complex weight vector at each sampling instant. But, the short time spectra analysis sometimes deals with the complex signal that is outputted from complex analog filter. So, in order to optimize and develop this methods, furthermore it is necessary to derive an algorithm for the complex analytical signal. In this paper, we first discuss the new adaptive system for the spectra analysis using the complex LMS algorithm and then derive convergence condition, time constant of coefficient adjustment and frequency resolution by extending the discussion. Finally, the effectiveness of the proposed method is experimentally demonstrated by applying it to the measurement of transfer performance on complex analog filter.

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