• KIPS Transactions on Software and Data Engineering
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• v.5 no.10
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• pp.503-510
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• 2016

FsGr model, which has been proposed recently, is an approach of accelerometer-based gesture recognition by applying DTW algorithm in two steps, which improved recognition success rate. In FsGr model, sets of similar gestures will be produced through training phase, in order to define the notion of a set of similar gestures. At the 1st attempt of gesture recognition, if the result turns out to belong to a set of similar gestures, it makes the 2nd recognition attempt to feature-strengthened parts extracted from the set of similar gestures. However, since a same gesture show drastically different characteristics according to physical traits such as body size, age, and sex, FsGr model may not be good enough to apply to multi-user environments. In this paper, we propose FsGrM model that extends FsGr model for multi-user environment and present a program which controls channel and volume of smart TV using FsGrM model.

• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.658-670
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• 2006

As the educational media tends to be more digitalized and individualized, the learning paradigm is dramatically changing into e-learning. Existing on-line courseware gives a learner more chances to learn when they are home with their own PCs. However, it is of little use when they are away from their digital media. Also, it is very labor-intensive to convert the original off-line contents to on-line contents. This paper proposes education mobile contents(EMC) that can supply the learners with dynamic interactions using various multimedia information by recognizing real images of off-line contents using mobile devices. Content-based image retrieval based on object shapes is used to recognize the real image, and shapes are represented by differential chain code with estimated new starting points to obtain rotation-invariant representation, which is fitted to computational resources of mobile devices with low resolution camera. Moreover we use a dynamic time warping method to recognize the object shape, which compensates scale variations of an object. The EMC can provide learners with quick and accurate on-line contents on off-line ones using mobile devices without limitations of space.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.173-173
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• 2021

현재까지 상수도관망 내 수질적 거동에 대한 분석은 (1) 네트워크 수질 모델(EPANET 수질모의 등)에 기반한 방법과 (2) 시공간적 저해상도 데이터에 기반한 데이터 분석법이 주를 이루었다. 그러나 현존 네트워크 수질 모델은 수질 사고의 복잡한 물리·화학적 거동을 상세히 모의하기 어렵다. 반면 계측 및 통신기술의 발달로 고해상도 수질 데이터의 실시간 수집이 가능해지면서 사고의 사전감지, 발생시 즉각적 탐지 및 대응을 위한 데이터 분석법에 관심이 증가하고 있다. 서울 문래동, 인천, 포항의 경우에서도 알 수 있듯이, 수질사고 발생 시 원인물질의 시공간적 이송 또는 전파에 대한 정보는 사고대응에 유용하게 활용된다. 본 연구는, 비정상적인 수질변화의 계통 내 전달 시간을 계산하기 위해 고해상도 수질 스마트 미터 데이터에 기반한 데이터 분석법을 개발하였다. 물공급 하류방향의 수질변화 전달 시간 정량화를 위해 화음탐색법 기반 동적시간워핑(Dynamic time warping; DTW) 기술을 이용하였고, 원데이터의 전처리를 위해 이동평균필터링을 수행하였다. 개발된 분석법은 A시 생산 및 배·급수과정의 감시지점에서 10초 단위로 계측된 다양한 수질변수(pH, 탁도, 잔류염소, 전기전도도, 수온 등)의 공간적 변이 전파시간을 결정하기 위해 적용되었다. 분석에 활용한 데이터는 데이터 통신 및 측정 기기에 의한 이상값과 운영상황의 변화에 따라 변동한 값을 처리하기 이전의 데이터이다. 데이터 품질에 의한 영향을 배제하기 위해 이상값이 발생하지 않은 기간을 파악한 후, 그 기간에 대하여 분석하였다. 계통 내 위계에 따라 두 지점의 측정값의 전파시간을 정량화한 결과, 지점에 따라 전파시간이 다르게 나타났다. 또한, 같은 두 지점에 적용한 결과라도 DTW를 적용하는 기간과 이동평균필터링의 크기에 따라 수질변화 전달 시간이 다르게 나타나는 것을 확인할 수 있었다. 본 연구에서 개발된 분석법은 다변량 수질변수 간의 영향관계를 파악하는데 확장 적용이 가능하다. 또한, 이 방법의 실시간 적용을 통해 동적으로 변화하는 전달시간을 주기적, 공간적으로 갱신하여 관망 수질 변화 모니터링이 가능하다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.9
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• pp.751-756
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• 2012

In this paper, we propose a foreground extraction and depth map generation method using a time-of-flight (TOF) depth camera. Although, the TOF depth camera captures the scene's depth information in real-time, it has a built-in noise and distortion. Therefore, we perform several preprocessing steps such as image enhancement, segmentation, and 3D warping, and then use the TOF depth data to generate the depth-discontinuity regions. Then, we extract the foreground object and generate the depth map as of the color image. The experimental results show that the proposed method efficiently generates the depth map even for the object boundary and textureless regions.

• IE interfaces
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• v.20 no.3
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• pp.288-297
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• 2007

Success of semiconductor/LCD industry depends on its yield and quality of product. For the purpose, FDC (Fault Detection and Classification) system is used to diagnose fault state in main manufacturing processes by monitoring time series data collected by equipment sensors which represent various conditions of the equipment. The data set is segmented at the start and end of each product lot processing by a trigger event module. However, in practice, segmented sensor data usually have the features of data asynchronization such as different start points, end points, and data lengths. Due to the asynchronization problem, false alarm (type I error) and missed alarm (type II error) occur frequently. In this paper, we propose a robust process fault detection system by integrating a process event detection method and a similarity measuring method based on dynamic time warping algorithm. An experiment shows that the proposed system is able to recognize abnormal condition correctly under the asynchronous data situation.

• Journal of the Korea Society of Computer and Information
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• v.23 no.5
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• pp.9-14
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• 2018

For an efficient management of electricity market and power systems, accurate forecasts for electricity demand are essential. Since there are many factors, either known or unknown, determining the realized loads, it is difficult to forecast the demands with the past time series only. In this paper we perform a cluster analysis on electricity demand data collected from Jan. 2000 to Dec. 2017. Our purpose of clustering on electricity demand data is that each cluster is expected to consist of data whose latent variables are same or similar values. Then, if properly clustered, it is possible to develop an accurate forecasting model for each cluster separately. To validate the feasibility of this approach for building better forecasting models, we clustered data with t-SNE. To apply t-SNE to time series data effectively, we adopt the dynamic time warping as a similarity measure. From the result of experiments, we found that several clusters are well observed and each cluster can be interpreted as a mix of well-known factors such as trends, seasonality and holiday effects and other unknown factors. These findings can motivate the approaches which build forecasting models with respect to each cluster independently.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.427-429
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• 2017

본 논문에서는 실시간으로 주행 중인 차량의 영상을 대상으로 ROI 영역을 추출하고 추출된 ROI 영역에 Warping 기법과 RANSAC 알고리즘을 적용하여 곡선 차선을 검출하는 방법을 제안한다. 제안된 방법은 실시간 영상에서 관심 영역을 ROI 영역으로 설정하고 영상의 원근감을 제거하기 위하여 Warping을 적용한다. Warping이 적용된 영상에서 차선의 밝기는 도로의 밝기보다 높다는 특징을 이용하여 노란색과 흰색 차선의 영역을 추출한다. 추출된 차선의 영역에서 곡선을 검출하기 위하여 RANSAC 알고리즘을 적용하여 곡선을 검출하기 위한 기준점을 설정한 후, 스플라인 기법을 적용하여 곡선을 검출한다. 실시간적으로 주행 중인 차량에서 촬영한 동영상을 대상으로 실험한 결과, 곡선 차선이 효과적으로 검출되었다. 따라서 제안된 방법이 자율 주행에 효율적으로 적용될 수 있는 가능성을 확인하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.7
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• pp.1380-1386
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• 2003

Speech recognition performance is degraded by the variation in vocal tract length among speakers. In this paper, we have used a vocal tract length normalization method wherein the frequency axis of the short-time spectrum associated with a speaker's speech is scaled to minimize the effects of speaker's vocal tract length on the speech recognition performance In order to normalize vocal tract length, we tried several frequency warping functions such as linear and piece-wise linear function. Variable interval piece-wise linear warping function is proposed to effectively model the variation of frequency axis scale due to the large variation of vocal tract length. Experimental results on TIDIGITS connected digits showed the dramatic reduction of word error rates from 2.15% to 0.53% by the proposed vocal tract normalization.

• ETRI Journal
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• v.44 no.1
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• pp.24-37
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• 2022

Virtual view synthesis, which generates novel views similar to the characteristics of actually acquired images, is an essential technical component for delivering an immersive video with realistic binocular disparity and smooth motion parallax. This is typically achieved in sequence by warping the given images to the designated viewing position, blending warped images, and filling the remaining holes. When considering 6DoF use cases with huge motion, the warping method in patch unit is more preferable than other conventional methods running in pixel unit. Regarding the prior case, the quality of synthesized image is highly relevant to the means of blending. Based on such aspect, we proposed a novel blending architecture that exploits the similarity of the directions of rays and the distribution of depth values. By further employing the proposed method, results showed that more enhanced view was synthesized compared with the well-designed synthesizers used within moving picture expert group (MPEG-I). Moreover, we explained the GPU-based implementation synthesizing and rendering views in the level of real time by considering the applicability for immersive video service.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.75-80
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• 2010

Noise handing is very important in voice recognition of vehicle environment. that has been studying about to hardware and software approach. hardware method that is noise filter circuit design, basically using Low-pass filter. it was shown a good result. and the side of software that has been developing about to algorithm for Noise canceler, NN(neural network), etc. in this paper we have analysis about to classified parameter pattern matting level for voice recognition on car noise environment that use of DTW(Dynamic Time Warping) which is applicable time series pattern recognition algorithm.