• Title/Summary/Keyword: time-warping

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Rendering Trees Using Billboarding Method with View Dependent Texture Re-creation in Real-Time (시점 종속적 빌보드 텍스쳐 재생성을 이용한 나무의 실시간 렌더링)

  • Min, Sung-Hwan;Kim, Chang-Hun
    • Journal of the Korea Computer Graphics Society
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    • v.8 no.4
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    • pp.9-16
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    • 2002
  • In this paper we propose an extended billboarding method for rendering trees. It's difficult circumstance that PC renders forest by general polygon rendering in real-time, because tree object consists of tremendous leaves and limbs. Our method re-creates an appropriate texture image by 3D image warping equation each frame, and we use it for a billboarding method. For speed up, we use warping method with a image pyramid and image caching.

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Improvement of Dynamic Time Warping Algorithm by Using Voice/Unvoiced/Silence Information (유성/무성/묵음 정보론 이용한 동적 시간 정합 알고리즘 개선)

  • Choi Min Seok;Han Hyun Bae;Hahn Min Soo
    • Proceedings of the Acoustical Society of Korea Conference
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    • spring
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    • pp.40-43
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    • 1999
  • 본 연구에서는 고립단어 인식시스템에 사용되고 있는 DTW(DynamicTimeWarping) 알고리즘의 계산량을 줄일 수 있는 방법을 제안한다. 일반적으로 고립단어 인식시 가장 인식률이 좋은 알고리즘은 DW라고 알려져 있으나, 인식대상어휘가 늘어나면 계산량이 비례해서 늘어나고 인식률이 저하되는 단점이 있으므로 일반적으로 200단어 이하의 어휘에만 사용되고 있다. 따라서 대상어휘를 감소시켜 계산량을 줄이기 위해 본 논문에서는 유성/무성/묵음 (V/U/S) 정보를 이용하여 코드워드를 구성하고 같은 코드워드에 해당되는 단어들을 추출해이들 만을 비교대상 어휘로 제한하므로서 DW 알고리즘을 적용할 대상 어휘수를 줄이는 방법을 사용하여 계산 속도를 향상시켰다 또한 입력 단어와 대상 단어와의 누적거리 계산 시 끝점 정보 뿐 만 아니라 유성/무성/묵음 경계 정보를 이용하여 piecewise DTW를 구현함으로서 탐색 영역을 축소함으로써 추가적인 계산량 감소가 가능하다. 따라서 상기 기법들을 이용하면 PC상에서도 DTW를 이용한 대어휘 고립단어 음성 인식기의 구현이 가능할 것이다.

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Performance Improvement of Speaker Recognition System Using Genetic Algorithm (유전자 알고리즘을 이용한 화자인식 시스템 성능 향상)

  • 문인섭;김종교
    • The Journal of the Acoustical Society of Korea
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    • v.19 no.8
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    • pp.63-67
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    • 2000
  • This paper deals with text-prompt speaker recognition based on dynamic time warping (DTW). The Genetic Algorithm was applied to the creation of reference patterns for suitable reflection of the speaker characteristics, one of the most important determinants in the fields of speaker recognition. In order to overcome the weakness of text-dependent and text-independent speaker recognition, the text-prompt type was suggested. Performed speaker identification and verification in close and open set respectively, hence the Genetic algorithm-based reference patterns had been proven to have better performance in both recognition rate and speed than that of conventional reference patterns.

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Efficient Processing of Subsequence Searching in Sequence Databases (시퀀스 데이터베이스를 위한 서브시퀀스 탐색의 효율적인 처리)

  • Park, Sang-Hyun;Kim, Sang-Wook;Park, Jeong-Il
    • Journal of Industrial Technology
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    • v.21 no.A
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    • pp.155-166
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    • 2001
  • This paper deals with the subsequence searching problem under time-warping. Our work is motivated by the observation that subsequence searches slow down quadratically as the average length of data sequences increases. To resolve this problem, the Segment-Based Approach for Subsequence Searches (SBASS) is proposed. The SBASS divides data and query sequences into a series of segments, and retrieves all data subsequences. Our segmentation scheme allows segments to have different lengths; thus we employ the time warping distance as a similarity measure for each segment pair. For efficient retrieval of similar subsequences, we extract feature vectors from all data segments exploiting their monotonically changing properties, and build a spatial index using feature vectors. The effectiveness of our approach is verified through extensive experiments.

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Designing and Implementing Clustering Method of Particulate Matter Data by Region (지역별 미세먼지 발생 데이터 클러스터링 메소드 설계 및 구현)

  • Moon, Ju-Hwan;Yoon, Hong-Sik
    • Proceedings of the Korean Society of Disaster Information Conference
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    • 2016.11a
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    • pp.424-425
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    • 2016
  • 본 연구는 우리나라의 지역별 미세먼지 발생 데이터에 대한 수집과 그에 대한 분석, 처리 방법에 대한 연구로 수집된 미세먼지 데이터에 대한 클러스터링 메소드를 설계하고 구현하는 것을 목표로한다. 본 연구에서는 기상청 산하의 30여개의 관측소에서 측정된 미세먼지 데이터를 기반으로 클러스터링 작업에 대한 전처리를 실시한다. 이러한 전 처리에는 각 관측소의 미세먼지 데이터의 시계열 그래프의 유사도를 비교하기 위하여 Dynamic Time Warping알고리즘을 활용하였으며 이를 통해 산출되는 DTW값을 통하여 유사도가 높은 미세먼지 측정 지역별 클러스터링을 수행해 클러스터링 군별 미세먼지 발생 원인에 대한 분석과 대비, 피해저감 방안등의 대책 마련을 위한 자료로서 활용됨을 목적으로 한다.

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Study on Vacuum Pump Monitoring Using MPCA Statistical Method (MPCA 기반의 통계기법을 이용한 진공펌프 상태진단에 관한 연구)

  • Sung D.;Kim J.;Jung W.;Lee S.;Cheung W.;Lim J.;Chung K.
    • Journal of the Korean Vacuum Society
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    • v.15 no.4
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    • pp.338-346
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    • 2006
  • In semiconductor process, it is so hard to predict an exact failure point of the vacuum pump due to its harsh operation conditions and nonlinear properties, which may causes many problems, such as production of inferior goods or waste of unnecessary materials. Therefore it is very urgent and serious problem to develop diagnostic models which can monitor the operation conditions appropriately and recognize the failure point exactly, indicating when to replace the vacuum pump. In this study, many influencing factors are totally considered and eventually the monitoring model using multivariate statistical methods is suggested. The pivotal algorithms are Multiway Principal Component Analysis(MPCA), Dynamic Time Warping Algorithm(DTW Algorithm), etc.

Driving Pattern Recognition System Using Smartphone sensor stream (스마트폰 센서스트림을 이용한 운전 패턴 인식 시스템)

  • Song, Chung-Won;Nam, Kwang-Woo;Lee, Chang-Woo
    • Journal of Korea Society of Industrial Information Systems
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    • v.17 no.3
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    • pp.35-42
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    • 2012
  • The database for driving patterns can be utilized in various system such as automatic driving system, driver safety system, and it can be helpful to monitor driving style. Therefore, we propose a driving pattern recognition system in which the sensor streams from a smartphone are recorded and used for recognizing driving events. In this paper we focus on the driving pattern recognition that is an essential and preliminary step of driving style recognition. We divide input sensor streams into 7 driving patterns such as, Left-turn(L), U-turn(U), Right-turn(R), Rapid-Braking(RB), Quick-Start(QS), Rapid-Acceleration (RA), Speed-Bump(SB). To classify driving patterns, first, a preprocessing step for data smoothing is followed by an event detection step. Last the detected events are classified by DTW(Dynamic Time Warping) algorithm. For assisting drivers we provide the classified pattern with the corresponding video stream which is recorded with its sensor stream. The proposed system will play an essential role in the safety driving system or driving monitoring system.

Real-Time Virtual-View Image Synthesis Algorithm Using Kinect Camera (키넥트 카메라를 이용한 실시간 가상 시점 영상 생성 기법)

  • Lee, Gyu-Cheol;Yoo, Jisang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38C no.5
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    • pp.409-419
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    • 2013
  • Kinect released by Microsoft in November 2010 is a motion sensing camera in xbox360 and gives depth and color images. However, Kinect camera also generates holes and noise around object boundaries in the obtained images because it uses infrared pattern. Also, boundary flickering phenomenon occurs. Therefore, we propose a real-time virtual-view video synthesis algorithm which results in a high-quality virtual view by solving these problems. In the proposed algorithm, holes around the boundary are filled by using the joint bilateral filter. Color image is converted into intensity image and then flickering pixels are searched by analyzing the variation of intensity and depth images. Finally, boundary flickering phenomenon can be reduced by converting values of flickering pixels into the maximum pixel value of a previous depth image and virtual views are generated by applying 3D warping technique. Holes existing on regions that are not part of occlusion region are also filled with a center pixel value of the highest reliability block after the final block reliability is calculated by using a block based gradient searching algorithm with block reliability. The experimental results show that the proposed algorithm generated the virtual view image in real-time.

Efficient Handwritten Character Verification Using an Improved Dynamic Time Warping Algorithm (개선된 동적 타임 워핑 알고리즘을 이용한 효율적인 필기문자 감정)

  • Jang, Seok-Woo;Park, Young-Jae;Kim, Gye-Young
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.7
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    • pp.19-26
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    • 2010
  • In this paper, we suggest a efficient handwritten character verification method in on-line environments which automatically analyses two input character string and computes their similarity degrees. The proposed algorithm first applies the circular projection method to input handwritten strings and extracts their representative features including shape, directions, etc. It then calculates the similarity between two character strings by using an improved dynamic time warping (DTW) algorithm. We improved the conventional DTW algorithm efficiently through adopting the branch-and-bound policy to the existing DTW algorithm which is well-known to produce good results in the various optimization problems. The experimental results to verify the performance of the proposed system show that the suggested handwritten character verification method operates more efficiently than the existing DTW and DDTW algorithms in terms of the speed.

Efficient Subsequence Searching in Sequence Databases : A Segment-based Approach (시퀀스 데이터베이스를 위한 서브시퀀스 탐색 : 세그먼트 기반 접근 방안)

  • Park, Sang-Hyun;Kim, Sang-Wook;Loh, Woong-Kee
    • Journal of KIISE:Databases
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    • v.28 no.3
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    • pp.344-356
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    • 2001
  • This paper deals with the subsequence searching problem under time-warping in sequence databases. Our work is motivated by the observation that subsequence searches slow down quadratically as the average length of data sequences increases. To resolve this problem, the Segment-Based Approach for Subsequence Searches (SBSS) is proposed. The SBASS divides data and query sequences into a series of segments, and retrieves all data subsequences that satisfy the two conditions: (1) the number of segments is the same as the number of segments in a query sequence, and (2) the distance of every segment pair is less than or equal to a tolerance. Our segmentation scheme allows segments to have different lengths; thus we employ the time warping distance as a similarity measure for each segment pair. For efficient retrieval of similar subsequences, we extract feature vectors from all data segments exploiting their monotonically changing properties, and build a spatial index using feature vectors. Using this index, queries are processed with the four steps: (1) R-tree filtering, (2) feature filtering, (3) successor filtering, and (4) post-processing. The effectiveness of our approach is verified through extensive experiments.

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