• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제4권3호
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• pp.143-150
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• 2015

스마트 디바이스가 보편화되면서 이에 내장된 가속도 센서를 사용한 제스처의 인식에 관한 연구가 주목받고 있다. 최근 가속도 센서 데이터 시컨스를 통한 제스처 인식에 Dynamic Time Warping(DTW) 기법이 사용되는데, 본 논문에서는 DTW 사용 시 제스처의 인식률을 높이기 위한 특징 강조형 제스처 인식(FsGr) 모델을 제안한다. FsGr 모델은 잘못 인식될 가능성이 높은 유사 제스처들의 집합에 대해 특징이 강조되는 데이터 시컨스의 부분들을 정의하고 이들에 대해 추가적인 DTW를 실행하여 인식률을 높인다. FsGr 모델의 훈련 과정에서는 유사 제스처들의 집합들을 정의하고 유사 제스처들의 특징들을 분석한다. 인식 과정에서는 DTW를 사용한 1차 인식 시도의 결과 제스처가 유사 제스처 집합에 속한 경우, 특징 분석 결과를 기반으로 한 추가적인 인식을 시도하여 인식률을 높인다. 알파베트 소문자에 대한 인식 실험을 통해 FsGr 모델의 성능 평가 결과를 보인다.

• 한국멀티미디어학회논문지
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• 제21권9호
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• pp.1119-1130
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• 2018

Writing letters or patterns on a virtual space by moving a person's gaze is called "eye writing," which is a promising tool for various human-computer interface applications. This paper investigates the use of conventional eye writing recognition algorithms for the purpose of user-independent recognition of eye-written characters. Two algorithms are presented to build the user-independent system: eye-written region extraction using wavelet coefficients and template generation. The experimental results of the proposed system demonstrated that with dynamic positional warping, an F1 score of 79.61% was achieved for 12 eye-written patterns, thereby indicating the possibility of user-independent use of eye writing.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2015년도 제46회 하계학술대회
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• pp.45-46
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• 2015

가전기기별 에너지 사용정보를 제공함으로써 가정에서 효율적인 에너지 사용을 유도할 수 있다. 가전기기별 사용정보를 효과적으로 제공하기 위해서는 NILM (Non-Intrusive Load Monitoring) 기법이 필요하다.본 논문에서는 개별 가전기기 분류단계에서 쓰이는 DTW(Dynamic Time Warping) 기법을 소개한다. DTW 기법은 다른 두 시계열 데이턴간의 유사도를 측정하는 패턴인식 기법 중 하나이다. 이 유사도를 이용하여 가전기기의 동작여부를 판별하고 분류를 수행한다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2007년도 추계종합학술대회
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• pp.977-980
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• 2007

본 논문은 인식된 컨테이너 식별자 문자열과 컨테이너 작업리스트를 비교하여 작업리스트와 인식된 컨테이너 식별자 문자열을 매칭하는 효율적인 방법을 소개하고자 한다. Dynamic Time Warping 기법을 이용하여 오인식되거나 인식이 되지 않은 문자에 대하여 오독률을 최소화할 수 있는 효율적인 방법을 제안한다. 기존의 문자열 비교방식에 비하여 제안하는 방법을 사용하였을 경우 더 나은 성능을 보였다.

• 말소리와 음성과학
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• 제14권1호
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• pp.29-36
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• 2022

The English word-final /rl/ cluster poses a particular problem for Korean learners of English because it is the sequence of two sounds, /r/ and /l/, which are not contrastive in Korean. This study compared the similarity distances between English and Korean speakers' /rl/ productions using the dynamic time warping (DTW) algorithm. The words with /rl/ (pearl, world) and without /rl/ (bird, word) were recorded by four English speakers and four Korean speakers, and compared pairwise. The F2-F1 trajectories, the acoustic correlate of velarized /l/, and F3 trajectories, the acoustic correlate of /r/, were examined. Formant analysis showed that English speakers lowered F2-F1 values toward the end of a word, unlike Korean speakers, suggesting the absence of /l/ in Korean speakers. In contrast, there was no significant difference in F3 values. Mixed-effects regression analyses of the DTW distances revealed that Korean speakers produced /r/ similarly to English speakers but failed to produce the velarized /l/ in /rl/ clusters.

• Journal of Information Processing Systems
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• 제14권4호
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• pp.851-876
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• 2018

Dynamic time warping (DTW) is the main algorithms for time series alignment. However, it is unsuitable for quasi-periodic time series. In the current situation, except the recently published the shape exchange algorithm (SEA) method and its derivatives, no other technique is able to handle alignment of this type of very complex time series. In this work, we propose a novel algorithm that combines the advantages of the SEA and the DTW methods. Our main contribution consists in the elevation of the DTW power of alignment from the lowest level (Class A, non-periodic time series) to the highest level (Class C, multiple-periods time series containing different number of periods each), according to the recent classification of time series alignment methods proposed by Boucheham (Int J Mach Learn Cybern, vol. 4, no. 5, pp. 537-550, 2013). The new method (quasi-periodic dynamic time warping [QP-DTW]) was compared to both SEA and DTW methods on electrocardiogram (ECG) time series, selected from the Massachusetts Institute of Technology - Beth Israel Hospital (MIT-BIH) public database and from the PTB Diagnostic ECG Database. Results show that the proposed algorithm is more effective than DTW and SEA in terms of alignment accuracy on both qualitative and quantitative levels. Therefore, QP-DTW would potentially be more suitable for many applications related to time series (e.g., data mining, pattern recognition, search/retrieval, motif discovery, classification, etc.).

• 전기학회논문지
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• 제59권6호
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• pp.1143-1149
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• 2010

In this study, we propose a novel method to detect and enhance the feature of ST-segment which offers the crucial information for the diagnosis of myocardial infarction and ischemia. With this aim, PQRST features of Electrocardiogram initially are detected and subsequently ST-segment are estimated. And Dynamic Time Warping(DTW) transformation is applied recursively to minimize the difference in time between ST-segments and calculate the minimum cumulative distance that decides the degree of similarity among ST-segments. As of the results, the inherent characteristic of ST-segment can be emphasized in terms of time parameter and thus the diagnostic features of a ST-segment can be revealed further.

• International Journal of Contents
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• 제7권1호
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• pp.14-22
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• 2011

Temporal Sign Language Recognition (TSLR) from hand motion is an active area of gesture recognition research in facilitating efficient communication with deaf people. TSLR systems consist of two stages: a motion sensing step which extracts useful features from signers' motion and a classification process which classifies these features as a performed sign. This work focuses on two of the research problems, namely unknown time varying signal of sign languages in feature extraction stage and computing complexity and time consumption in classification stage due to a very large sign sequences database. In this paper, we propose a combination of Dynamic Time Warping (DTW) and application of the Single hidden Layer Feedforward Neural networks (SLFNs) trained by Extreme Learning Machine (ELM) to cope the limitations. DTW has several advantages over other approaches in that it can align the length of the time series data to a same prior size, while ELM is a useful technique for classifying these warped features. Our experiment demonstrates the efficiency of the proposed method with the recognition accuracy up to 98.67%. The proposed approach can be generalized to more detailed measurements so as to recognize hand gestures, body motion and facial expression.

• 한국지능시스템학회논문지
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• 제16권6호
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• pp.665-670
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• 2006

본 논문에서는, 동적 서명의 여러 가지 중요한 특징을 잘 반영할 수 있는 특징 정보를 추출하였고, 두 패턴을 비교하는 방법에서는 기존의 DTW 방법에서의 문제점을 개선하여 제안된 DTW 방법을 사용함으로써, 낮은 오류율(본인 거부율, 타인 수락률), 적은 량의 특징 정보, 빠른 처리 속도 등에서의 성능을 개선하였다.

• 한국측량학회지
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• 제35권5호
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• pp.329-338
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• 2017

This study attempts to classify 1008 alley markets in Seoul through cluster analysis using Dynamic Time Warping, one of the methods used to analyze the similarity of time series, and evaluate the possibility of opening new stores. The sequence of the gross sales of an alley market and that of gross sales per store stand for the potential of growth and profitability of the market, respectively and are used as variables for cluster analysis. Five clusters are obtained for the gross sales and four clusters for the gross sales per store. These two types of clusters are again classified as rising and falling trends, respectively, and the combination of these trends produces four categories. These categories are used to evaluate the possibility of opening new stores in alley markets. The results show that the southeast which is relatively wealthy inferior to other regions in opening new stores. Alley markets in the northeast and the southwest are better than other regions such that opening a new store is justified. In the northwest, there are many markets with trend of gross sales and that of gross sales per store moving in opposite directions, and new store openings in these markets should be postponed.