• Journal of Industrial Technology
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• v.21 no.A
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• pp.167-179
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• 2001

This paper discusses an index-based subsequence matching that supports time warping in large sequence databases. Time warping enables finding sequences with similar patterns even when they are of different lengths. In earlier work, we suggested an efficient method for whole matching under time warping. This method constructs a multidimensional index on a set of feature vectors, which are invariant to time warping, from data sequences. For filtering at feature space, it also applies a lower-bound function, which consistently underestimates the time warping distance as well as satisfies the triangular inequality. In this paper, we incorporate the prefix-querying approach based on sliding windows into the earlier approach. For indexing, we extract a feature vector from every subsequence inside a sliding window and construct a multi-dimensional index using a feature vector as indexing attributes. For query precessing, we perform a series of index searches using the feature vectors of qualifying query prefixes. Our approach provides effective and scalable subsequence matching even with a large volume of a database. We also prove that our approach does not incur false dismissal. To verily the superiority of our method, we perform extensive experiments. The results reseal that our method achieves significant speedup with real-world S&P 500 stock data and with very large synthetic data.

• Journal of Digital Contents Society
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• v.16 no.2
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• pp.235-244
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• 2015

This study proposes a leaf modeling method that uses feature-based warping for efficient generation of various digital leaves. The proposed method uses warping method, one of image processing application techniques that can control various shapes of leaves in an easy, intuitive way, and generate natural patterns of veins efficiently. First, information on approximated contour is detected from a leaf blade image to identify the shape of a blade. Based on this, control line is automatically calculated to be used for feature-based warping. Then, control line-based warping is conducted to modify forms of leaf blade images in an intuitive way, automatically generating leaves of various shapes. And natural vein patterns are generated by applying a contour-based venation growth algorithm from contour information of the modified leaf blade images. This study performs experiments to verify whether various shape of leaves that comprise plants can be efficiently generated using a sample binary image of a blade. Also, we demonstrate that express the natural growth of leaves by applying warping to the growth of the leaf blade.

• Journal of Korea Multimedia Society
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• v.11 no.6
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• pp.777-786
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• 2008

Human face avatar is important information in nowadays, such as describing real people in virtual world. In this paper, we have presented a face avatar creation and warping algorithm by using face feature analysis method, in order to detect face feature, we utilized local mean method based on facial feature appearance and face geometric information. Then detect facial candidates by using it's character in $YC_bC_r$ color space. Meanwhile, we also defined the rules which are based on face geometric information to limit searching range. For analyzing face feature, we used face feature points to describe their feature, and analyzed geometry relationship of these feature points to create the face avatar. Then we have carried out simulation on PC and embed mobile device such as PDA and mobile phone to evaluate efficiency of the proposed algorithm. From the simulation results, we can confirm that our proposed algorithm will have an outstanding performance and it's execution speed can also be acceptable.

• Journal of Industrial Technology
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• v.20 no.B
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• pp.219-226
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• 2000

In this paper, we propose a new novel method for similarity search that supports time warping. Our primary goal is to innovate on search performance in large databases without false dismissal. To attain this goal, we devise a new distance function $D_{tw-lb}$ that consistently underestimates the time warping distance and also satisfies the triangular inequality. $D_{tw-lb}$ uses a 4-tuple feature vector extracted from each sequence and is invariant to time warping. For efficient processing, we employ a multidimensional index that uses the 4-tuple feature vector as indexing attributes and $D_{tw-lb}$ as a distance function. We prove that our method does not incur false dismissal. To verify the superiority of our method, we perform extensive experiments. The results reveal that our method achieves significant speedup up to 43 times with real-world S&P 500 stock data.

• Journal of Korea Game Society
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• v.14 no.2
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• pp.55-66
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• 2014

Image warping is a technology to transform input images to be suitable for given conditions and has been recently utilized in changing face shape of characters in the field of movies or animation. Mesh warping which is one of warping methods that change shapes based on the features of face forms warping images by forming rectangular mesh groups around the eyes, nose, and mouth and matching them 1:1. This method has a problem in the resultant images are distorted in the segments of boundaries between meshes when there are errors in mesh control points or when meshes have been formed as many small area meshes. This study proposes a triangle based image interpolation technique to minimize the occurrence of errors in the process of forming natural warping images of face and process accurate results with a small amount of arithmetic operation and a short time. First, feature points that represent the face are found and these points are connected to form basic triangle meshes. The fact that the proposed method can reduce errors occurring in the process of warping while reducing the amount of arithmetic operation and time is shown through experiments.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.3
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• pp.143-150
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• 2015

As smart devices get popular, research on gesture recognition using their embedded-accelerometer draw attention. As Dynamic Time Warping(DTW), recently, has been used to perform gesture recognition on data sequence from accelerometer, in this paper we propose Feature-Strengthened Gesture Recognition(FsGr) Model which can improve the recognition success rate when DTW is used. FsGr model defines feature-strengthened parts of data sequences to similar gestures which might produce unsuccessful recognition, and performs additional DTW on them to improve the recognition rate. In training phase, FsGr model identifies sets of similar gestures, and analyze features of gestures per each set. During recognition phase, it makes additional recognition attempt based on the result of feature analysis to improve the recognition success rate, when the result of first recognition attempt belongs to a set of similar gestures. We present the performance result of FsGr model, by experimenting the recognition of lower case alphabets.

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.173-184
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• 2002

This paper discuss an index-based subsequence matching that supports time warping in large sequence databases. Time warping enables finding sequences with similar patterns even when they are of different lengths. In earlier work, Kim et al. suggested an efficient method for whole matching under time warping. This method constructs a multidimensional index on a set of feature vectors, which are invariant to time warping, from data sequences. For filtering at feature space, it also applies a lower-bound function, which consistently underestimates the time warping distance as well as satisfies the triangular inequality. In this paper, we incorporate the prefix-querying approach based on sliding windows into the earlier approach. For indexing, we extract a feature vector from every subsequence inside a sliding window and construct a multidimensional index using a feature vector as indexing attributes. For query processing, we perform a series of index searches using the feature vectors of qualifying query prefixes. Our approach provides effective and scalable subsequence matching even with a large volume of a database. We also prove that our approach does not incur false dismissal. To verify the superiority of our approach, we perform extensive experiments. The results reveal that our approach achieves significant speedup with real-world S&P 500 stock data and with very large synthetic data.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.215-218
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• 2003

The method of vocal tract normalization has been known as a successful method for improving the accuracy of speech recognition. A frequency warping procedure based low complexity and maximum likelihood has been generally applied for vocal tract normalization. In this paper, we propose a new power spectrum warping procedure that can be improve on vocal tract normalization performance than a frequency warping procedure. A mechanism for implementing this method can be simply achieved by modifying the power spectrum of filter bank in Mel-frequency cepstrum feature(MFCC) analysis. Experimental study compared our Proposal method with the well-known frequency warping method. The results have shown that the power spectrum warping is better 50% about the recognition performance than the frequency warping.

• Phonetics and Speech Sciences
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• v.7 no.1
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• pp.3-10
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• 2015

In this paper, different frequency scales in cepstral feature extraction are evaluated for the text-independent speaker recognition. To this end, mel-frequency cepstral coefficients (MFCCs), linear frequency cepstral coefficients (LFCCs), and bilinear warped frequency cepstral coefficients (BWFCCs) are applied to the speaker recognition experiment. In addition, the spectro-temporal features extracted by the cepstral-time matrix (CTM) are examined as an alternative to the delta and delta-delta features. Experiments on the NIST speaker recognition evaluation (SRE) 2004 task are carried out using the Gaussian mixture model-universal background model (GMM-UBM) method and the joint factor analysis (JFA) method, both based on the ALIZE 3.0 toolkit. Experimental results using both the methods show that BWFCC with appropriate warping factor yields better performance than MFCC and LFCC. It is also shown that the feature set including the spectro-temporal information based on the CTM outperforms the conventional feature set including the delta and delta-delta features.

• 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.