• Title/Summary/Keyword: 가우시안 모델링

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Noise filtering for Depth Images using Shape Smoothing and Z-buffer Rendering (형상 스무딩과 Z-buffer 렌더링을 이용한 깊이 영상의 노이즈 필터링)

  • Kim, Seung-Man;Park, Jeung-Chul;Cho, Ji-Ho;Lee, Kwan-H.
    • 한국HCI학회:학술대회논문집
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    • 2006.02a
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    • pp.1188-1193
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    • 2006
  • 본 논문에서는 동적 객체의 3 차원 정보를 표현하는 깊이 영상의 노이즈 필터링 방법을 제안한다. 실제 객체의 동적인 3 차원 정보는 적외선 깊이 센서가 장착된 깊이 비디오 카메라를 이용하여 실시간으로 획득되며, 일련의 깊이 영상, 즉 깊이 비디오(depth video)로 표현될 수 있다. 하지만 측정환경의 조명조건, 객체의 반사속성, 카메라의 시스템 오차 등으로 인해 깊이 영상에는 고주파 성분의 노이즈가 발생하게 된다. 이를 효과적으로 제거하기 위해 깊이 영상기반의 모델링 기법(depth image-based modeling)을 이용한 3 차원 메쉬 모델링을 수행한다. 생성된 3 차원 메쉬 모델은 깊이 영상의 노이즈로 인해 경계 영역과 형상 내부 영역에 심각한 형상 오차를 가진다. 경계 영역의 오차를 제거하기 위해 깊이 영상으로부터 경계 영역을 추출하고, 가까운 순서로 정렬한 후 angular deviation 을 이용하여 불필요하게 중복된 점들을 제거한다. 그리고 나서 2 차원 가우시안 스무딩 기법을 적용하여 부드러운 경계영역을 생성한다. 형상 내부에 대해서는 경계영역에 제약조건을 주고 3 차원 가우시안 스무딩 기법을 적용하여 전체적으로 부드러운 형상을 생성한다. 최종적으로 스무딩된 3 차원 메쉬모델을 렌더링할 때, 깊이 버퍼에 있는 정규화된 깊이 값들을 추출하여 원래 깊이 영상과 동일한 깊이 영역을 가지도록 저장함으로서 전역적으로 연속적이면서 부드러운 깊이 영상을 생성할 수 있다. 제안된 방법에 의해 노이즈가 제거된 깊이 영상을 이용하여 고품질의 영상기반 렌더링이나 깊이 비디오 기반의 햅틱 렌더링에 적용할 수 있다.

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An Efficient Slant Correction for Handwritten Hangul Strings using Structural Properties (한글필기체의 구조적 특징을 이용한 효율적 기울기 보정)

  • 유대근;김경환
    • Journal of KIISE:Software and Applications
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    • v.30 no.1_2
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    • pp.93-102
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    • 2003
  • A slant correction method for handwritten Korean strings based on analysis of stroke distribution, which effectively reflects structural properties of Korean characters, is presented in this paper. The method aims to deal with typical problems which have been frequently observed in slant correction of handwritten Korean strings with conventional approaches developed for English/European languages. Extracted strokes from a line of text image are classified into two clusters by applying the K-means clustering. Gaussian modeling is applied to each of the clusters and the slant angle is estimated from the model which represents the vertical strokes. Experimental results support the effectiveness of the proposed method. For the performance comparison 1,300 handwritten address string images were used, and the results show that the proposed method has more superior performance than other conventional approaches.

Speaker Recognition Performance Improvement by Voiced/Unvoiced Classification and Heterogeneous Feature Combination (유/무성음 구분 및 이종적 특징 파라미터 결합을 이용한 화자인식 성능 개선)

  • Kang, Jihoon;Jeong, Sangbae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.6
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    • pp.1294-1301
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    • 2014
  • In this paper, separate probabilistic distribution models for voiced and unvoiced speech are estimated and utilized to improve speaker recognition performance. Also, in addition to the conventional mel-frequency cepstral coefficient, skewness, kurtosis, and harmonic-to-noise ratio are extracted and used for voiced speech intervals. Two kinds of scores for voiced and unvoiced speech are linearly fused with the optimal weight found by exhaustive search. The performance of the proposed speaker recognizer is compared with that of the conventional recognizer which uses mel-frequency cepstral coefficient and a unified probabilistic distribution function based on the Gassian mixture model. Experimental results show that the lower the number of Gaussian mixture, the greater the performance improvement by the proposed algorithm.

Adaptive Counting Line Detection for Traffic Analysis in CCTV Videos (CCTV영상 내 교통량 분석을 위한 적응적 계수선 검출 방법)

  • Jung, Hyeonseok;Lim, Seokjae;Lee, Ryong;Park, Minwoo;Lee, Sang-Hwan;Kim, Wonjun
    • Journal of Broadcast Engineering
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    • v.25 no.1
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    • pp.48-57
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    • 2020
  • Recently, with the rapid development of image recognition technology, the demand for object analysis in road CCTV videos is increasing. In this paper, we propose a method that can adaptively find the counting line for traffic analysis in road CCTV videos. First, vehicles on the road are detected, and the corresponding positions of the detected vehicles are modeled as the two-dimensional pointwise Gaussian map. The paths of vehicles are estimated by accumulating pointwise Gaussian maps on successive video frames. Then, we apply clustering and linear regression to the accumulated Gaussian map to find the principal direction of the road, which is highly relevant to the counting line. Experimental results show that the proposed method for detecting the counting line is effective in various situations.

Active Object Tracking based on stepwise application of Region and Color Information (지역정보와 색 정보의 단계적 적용에 의한 능동 객체 추적)

  • Jeong, Joon-Yong;Lee, Kyu-Won
    • The KIPS Transactions:PartB
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    • v.19B no.2
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    • pp.107-112
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    • 2012
  • An active object tracking algorithm using Pan and Tilt camera based in the stepwise application of region and color information from realtime image sequences is proposed. To reduce environment noises in input sequences, Gaussian filtering is performed first. An image is divided into background and objects by using the adaptive Gaussian mixture model. Once the target object is detected, an initial search window close to an object region is set up and color information is extracted from the region. We track moving objects in realtime by using the CAMShift algorithm which enables to trace objects in active camera with the color information. The proper tracking is accomplished by controlling the amount of pan and tilt to be placed the center position of object into the middle of field of view. The experimental results show that the proposed method is more effective than the hand-operated window method.

Natural Scene Text Binarization using Tensor Voting and Markov Random Field (텐서보팅과 마르코프 랜덤 필드를 이용한 자연 영상의 텍스트 이진화)

  • Choi, Hyun Su;Lee, Guee Sang
    • Smart Media Journal
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    • v.4 no.4
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    • pp.18-23
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    • 2015
  • In this paper, we propose a method for detecting the number of clusters. This method can improve the performance of a gaussian mixture model function in conventional markov random field method by using the tensor voting. The key point of the proposed method is that extracts the number of the center through the continuity of saliency map of the input data of the tensor voting token. At first, we separate the foreground and background region candidate in a given natural images. After that, we extract the appropriate cluster number for each separate candidate regions by applying the tensor voting. We can make accurate modeling a gaussian mixture model by using a detected number of cluster. We can return the result of natural binary text image by calculating the unary term and the pairwise term of markov random field. After the experiment, we can confirm that the proposed method returns the optimal cluster number and text binarization results are improved.

The Performance Analysis of Trellis-coded ${\pi}$/8-shift in Digital Mobile Communication (디지틀 이동통신에서 trellis-부호화된 ${\pi}$/8-shift 8PSK 변조방식의 성능 분석)

  • 황인태;김한종;강민구;김종일;홍대식;강창언
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.1
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    • pp.69-82
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    • 1993
  • 본 논문에서는 디지틀 이동 통신 시스템의 열악한 페이딩 채널에 적합한 변복조 반식중의 하나인${\pi}$/4-shift QPSK 성능을 논하고, 그 성능 개선을 위한 새로운 TCM(trellis-coded modulation)을 적응하여 trellis-부호화된${\pi}$/8-shift 8SPSK 방식을 제안 한다. 기존의 ${\pi}$/4-shift QPSK변조 방식에 TCM의 도입은 요구된 대역폭과 송신 전력과 전송을 그대로 유지하면서 부호화와 변조를 일체화함으로서 부호화 이득(coding gain)을 얻을 수 있다. 이동 통신 채널에서 trellis-부호화된 ${\pi}$/8-shift 8PSK방식의 시스템 성능을 추정하기 위해서, 가산 백색 가우시안 잡음과 레일레이 페이딩 현상이 존재하는 채널에서, 차량속도 변화에 따른 도플러 효과에 의한 페이딩율이 10Hz와 30Hz인 두 경우에 대해 시스템을 모델링한다. Trellis-부호화된${\pi}$/8-shift 8PSK에 대한 부호화 이득은 비트 에러 확률을 적용하여 분석하고, 기본 시스템과 새롭게 모델링 되어진 시스템의 개선된 성능을 비교하기 위해, TCM의 상태수를 4,8,16으로 선정하여 비교 구현해 본 결과, 상태수가 커질수록 더 좋은 성능을 나타내고, 기존의 ${\pi}$/4-shift QPSK보다 trellis-부호된 ${\pi}$/8-shift 8PSK는 가산 백색 가우시안 잡음채널에서는 3~4dB의 부호화 이득을 얻고, 레일레이 페이티 채널하에서 3~16dB정도의 부호화 이득을 얻음을 알 수 있다.

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Illumination Influence Minimization Method for Efficient Object (영상에서 효율적인 객체 추출을 위한 조명 영향 최소화 기법)

  • Kim, Jae-Seoung;Lee, Ki-Jung;Whangbo, Taeg-Keun
    • Journal of Digital Contents Society
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    • v.14 no.1
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    • pp.117-124
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    • 2013
  • This paper suggests the robust method of extraction for moving objects in illumination variation by using image sequence from an immovable camera. The most difficult part of the implication is the effect by illumination and noise. The object area is hardly estimated when the dusky area occurs in illumination variation by time change. This thesis describes the extraction of moving objects employed by Gaussian mixture model which is noise robust measure. Also, the report suggests the elimination method of illumination part in input image by the representative illumination image which is defined to minimize the illumination influence.

Performance Analysis of the M-PPAM DS-UWB Communication systems (M-PPAM DS-UWB 통신시스템의 성능해석)

  • Cho, Kyung-Ryong;Park, Jang-Woo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.8
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    • pp.1656-1662
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    • 2005
  • This paper introduces M-PPAM(M-ary Pulse Position and Amplitude Modulation) architecture, combined PPM(Pulse Position Modulation) with PAM(Pulse Amplitude Modulation). Since M-PPAM can transmit several bits using one pulse, it is mon effective than PPM or PAM. Also, to obtain the same data transmission rate with PPM or PAM, M-PPAM can use a long pulse repetition period. This method will be able to use in the multi-path fading environment such as indoor condition. To accomodate multiple users, direct sequence technique is used. This paper has provided the modeling method of the M-PPAM DS-UWB receiver covering multi-user interference(MUI) with the Standard Gaussian Approximation under Gaussian channel. The performance of the receiver is simulated.

Gaussian Mixture based K2 Rifle Chamber Pressure Modeling of M193 and K100 Bullets (가우시안 혼합모델 기반 탄종별 K2 소화기의 약실압력 모델링)

  • Kim, Jong-Hwan;Lee, Byounghwak;Kim, Kyoungmin;Shin, Kyuyong;Lee, Wonwoo
    • Journal of the Korea Institute of Military Science and Technology
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    • v.22 no.1
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    • pp.27-34
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    • 2019
  • This paper presents a chamber pressure model development of K2 rifle by applying Gaussian mixture model. In order to materialize a real recoil force of a virtual reality shooting rifle in military combat training, the chamber pressure which is one of major components of the recoil force needs to be investigated and modeled. Over 200,000 data of the chamber pressure were collected by implementing live fire experiments with both K100 and M193 of 5.56 mm bullets. Gaussian mixture method was also applied to create a mathematical model that satisfies nonlinear, asymmetry, and deviations of the chamber pressure which is caused by irregular characteristics of propellant combustion. In addition, Polynomial and Fourier Regression were used for comparison of results, and the sum of squared errors, the coefficient of determination and root-mean-square errors were analyzed for performance measurement.