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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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The KIPS Transactions:PartB
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Korea Information Processing Society
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Volume & Issues
Volume 16B, Issue 6 - Dec 2009
Volume 16B, Issue 5 - Oct 2009
Volume 16B, Issue 4 - Aug 2009
Volume 16B, Issue 3 - Jun 2009
Volume 16B, Issue 2 - Apr 2009
Volume 16B, Issue 1 - Feb 2009
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Inexpensive Visual Motion Data Glove for Human-Computer Interface Via Hand Gesture Recognition
Han, Young-Mo ;
The KIPS Transactions:PartB, volume 16B, issue 5, 2009, Pages 341~346
DOI : 10.3745/KIPSTB.2009.16B.5.341
The motion data glove is a representative human-computer interaction tool that inputs human hand gestures to computers by measuring their motions. The motion data glove is essential equipment used for new computer technologiesincluding home automation, virtual reality, biometrics, motion capture. For its popular usage, this paper attempts to develop an inexpensive visual.type motion data glove that can be used without any special equipment. The proposed approach has the special feature; it can be developed as a low-cost one becauseof not using high-cost motion-sensing fibers that were used in the conventional approaches. That makes its easy production and popular use possible. This approach adopts a visual method that is obtained by improving conventional optic motion capture technology, instead of mechanical method using motion-sensing fibers. Compared to conventional visual methods, the proposed method has the following advantages and originalities Firstly, conventional visual methods use many cameras and equipments to reconstruct 3D pose with eliminating occlusions But the proposed method adopts a mono vision approachthat makes simple and low cost equipments possible. Secondly, conventional mono vision methods have difficulty in reconstructing 3D pose of occluded parts in images because they have weak points about occlusions. But the proposed approach can reconstruct occluded parts in images by using originally designed thin-bar-shaped optic indicators. Thirdly, many cases of conventional methods use nonlinear numerical computation image analysis algorithm, so they have inconvenience about their initialization and computation times. But the proposed method improves these inconveniences by using a closed-form image analysis algorithm that is obtained from original formulation. Fourthly, many cases of conventional closed-form algorithms use approximations in their formulations processes, so they have disadvantages of low accuracy and confined applications due to singularities. But the proposed method improves these disadvantages by original formulation techniques where a closed-form algorithm is derived by using exponential-form twist coordinates, instead of using approximations or local parameterizations such as Euler angels.
Motion Plane Estimation for Real-Time Hand Motion Recognition
Jeong, Seung-Dae ; Jang, Kyung-Ho ; Jung, Soon-Ki ;
The KIPS Transactions:PartB, volume 16B, issue 5, 2009, Pages 347~358
DOI : 10.3745/KIPSTB.2009.16B.5.347
In this thesis, we develop a vision based hand motion recognition system using a camera with two rotational motors. Existing systems were implemented using a range camera or multiple cameras and have a limited working area. In contrast, we use an uncalibrated camera and get more wide working area by pan-tilt motion. Given an image sequence provided by the pan-tilt camera, color and pattern information are integrated into a tracking system in order to find the 2D position and direction of the hand. With these pose information, we estimate 3D motion plane on which the gesture motion trajectory from approximately forms. The 3D trajectory of the moving finger tip is projected into the motion plane, so that the resolving power of the linear gesture patterns is enhanced. We have tested the proposed approach in terms of the accuracy of trace angle and the dimension of the working volume.
A Study of Flexible Protein Structure Alignment Using Three Dimensional Local Similarities
Park, Chan-Yong ; Hwang, Chi-Jung ;
The KIPS Transactions:PartB, volume 16B, issue 5, 2009, Pages 359~366
DOI : 10.3745/KIPSTB.2009.16B.5.359
Analysis of 3-dimensional (3D) protein structure plays an important role of structural bioinformatics. The protein structure alignment is the main subjects of the structural bioinformatics and the most fundamental problem. Protein Structures are flexible and undergo structural changes as part of their function, and most existing protein structure comparison methods treat them as rigid bodies, which may lead to incorrect alignment. We present a new method that carries out the flexible structure alignment by means of finding SSPs(Similar Substructure Pairs) and flexible points of the protein. In order to find SSPs, we encode the coordinates of atoms in the backbone of protein into RDA(Relative Direction Angle) using local similarity of protein structure. We connect the SSPs with Floyd-Warshall algorithm and make compatible SSPs. We compare the two compatible SSPs and find optimal flexible point in the protein. On our well defined performance experiment, 68 benchmark data set is used and our method is better than three widely used methods (DALI, CE, FATCAT) in terms of alignment accuracy.
Flame Detection Using Haar Wavelet and Moving Average in Infrared Video
Kim, Dong-Keun ;
The KIPS Transactions:PartB, volume 16B, issue 5, 2009, Pages 367~376
DOI : 10.3745/KIPSTB.2009.16B.5.367
In this paper, we propose a flame detection method using Haar wavelet and moving averages in outdoor infrared video sequences. Our proposed method is composed of three steps which are Haar wavelet decomposition, flame candidates detection, and their tracking and flame classification. In Haar wavelet decomposition, each frame is decomposed into 4 sub- images(LL, LH, HL, HH), and also computed high frequency energy components using LH, HL, and HH. In flame candidates detection, we compute a binary image by thresholding in LL sub-image and apply morphology operations to the binary image to remove noises. After finding initial boundaries, final candidate regions are extracted using expanding initial boundary regions to their neighborhoods. In tracking and flame classification, features of region size and high frequency energy are calculated from candidate regions and tracked using queues, and we classify whether the tracked regions are flames by temporal changes of moving averages.
Segmentation and Contents Classification of Document Images Using Local Entropy and Texture-based PCA Algorithm
Kim, Bo-Ram ; Oh, Jun-Taek ; Kim, Wook-Hyun ;
The KIPS Transactions:PartB, volume 16B, issue 5, 2009, Pages 377~384
DOI : 10.3745/KIPSTB.2009.16B.5.377
A new algorithm in order to classify various contents in the image documents, such as text, figure, graph, table, etc. is proposed in this paper by classifying contents using texture-based PCA, and by segmenting document images using local entropy-based histogram. Local entropy and histogram made the binarization of image document not only robust to various transformation and noise, but also easy and less time-consuming. And texture-based PCA algorithm for each segmented region was taken notice of each content in the image documents having different texture information. Through this, it was not necessary to establish any pre-defined structural information, and advantages were found from the fact of fast and efficient classification. The result demonstrated that the proposed method had shown better performances of segmentation and classification for various images, and is also found superior to previous methods by its efficiency.
A New Face Tracking and Recognition Method Adapted to the Environment
Ju, Myung-Ho ; Kang, Hang-Bong ;
The KIPS Transactions:PartB, volume 16B, issue 5, 2009, Pages 385~394
DOI : 10.3745/KIPSTB.2009.16B.5.385
Face tracking and recognition are difficult problems because the face is a non-rigid object. The main reasons for the failure to track and recognize the faces are the changes of a face pose and environmental illumination. To solve these problems, we propose a nonlinear manifold framework for the face pose and the face illumination normalization processing. Specifically, to track and recognize a face on the video that has various pose variations, we approximate a face pose density to single Gaussian density by PCA(Principle Component Analysis) using images sampled from training video sequences and then construct the GMM(Gaussian Mixture Model) for each person. To solve the illumination problem for the face tracking and recognition, we decompose the face images into the reflectance and the illuminance using the SSR(Single Scale Retinex) model. To obtain the normalized reflectance, the reflectance is rescaled by histogram equalization on the defined range. We newly approximate the illuminance by the trained manifold since the illuminance has almost variations by illumination. By combining these two features into our manifold framework, we derived the efficient face tracking and recognition results on indoor and outdoor video. To improve the video based tracking results, we update the weights of each face pose density at each frame by the tracking result at the previous frame using EM algorithm. Our experimental results show that our method is more efficient than other methods.
Robust Facial Expression-Recognition Against Various Expression Intensity
Kim, Jin-Ok ;
The KIPS Transactions:PartB, volume 16B, issue 5, 2009, Pages 395~402
DOI : 10.3745/KIPSTB.2009.16B.5.395
This paper proposes an approach of a novel facial expression recognition to deal with different intensities to improve a performance of a facial expression recognition. Various expressions and intensities of each person make an affect to decrease the performance of the facial expression recognition. The effect of different intensities of facial expression has been seldom focused on. In this paper, a face expression template and an expression-intensity distribution model are introduced to recognize different facial expression intensities. These techniques, facial expression template and expression-intensity distribution model contribute to improve the performance of facial expression recognition by describing how the shift between multiple interest points in the vicinity of facial parts and facial parts varies for different facial expressions and its intensities. The proposed method has the distinct advantage that facial expression recognition with different intensities can be very easily performed with a simple calibration on video sequences as well as still images. Experimental results show a robustness that the method can recognize facial expression with weak intensities.
A Heuristic Algorithm for the Two-Dimensional Bin Packing Problem Using a Fitness Function
Yon, Yong-Ho ; Lee, Sun-Young ; Lee, Jong-Yun ;
The KIPS Transactions:PartB, volume 16B, issue 5, 2009, Pages 403~410
DOI : 10.3745/KIPSTB.2009.16B.5.403
The two-dimensional bin packing problem(2D-BPP) has been known to be NP-hard, and it is difficult to solve the problem exactly. Many approximation methods, such as genetic algorithm, simulated annealing and tabu search etc, have been also proposed to gain better solutions. However, the existing approximation algorithms, such as branch-and-bound and tabu search, have shown the low efficiency and the long execution time due to a large of iterations. To solve these problems, we first define the fitness function to simplify and increase the utility of algorithm. The function decides whether an item is packed into a given area, and as an important information for a packing strategy, the number of subarea that can accommodate a given item is obtained from the variant of the fitness function. Then we present a heuristic algorithm BF for 2D bin packing, constructed by the fitness function and subarea. Finally, the effectiveness of the proposed algorithm will be expressed by the comparison experiments with the heuristic and the metaheuristic of the literatures. As comparing with existing heuristic algorithms and metaheuristic algorithms, it has been found that the packing rate of algorithm BP is the same as 97% as existing heuristic algorithms, FFF and FBS, or better than them. Also, it has been shown the same as 86% as tabu search algorithm or better.
Mine Algorithm : A Metaheuristic Imitating The Action of The Human Being
Ko, Sung-Bum ;
The KIPS Transactions:PartB, volume 16B, issue 5, 2009, Pages 411~426
DOI : 10.3745/KIPSTB.2009.16B.5.411
Most of the metaheuristics are made by imitating the action of the animals. In this paper, we proposed Mine Algorithm. The Mine Algorithm is a metaheuristic that imitates the action of the human being. Speaking of search, the field in which the know-how and the heuristics of the human being are melted best is the mining industry. In the Mine Algorithm we formalize the action pattern of the human being by focusing the mine business. The Mine Algorithm uses various searching techniques fluently and shows equally good performance for broad problems. That is, it has good generality. We show the improved generality of the Mine Algorithm by the comparing experiments with the conventional metaheuristics.
A Spelling Error Correction Model in Korean Using a Correction Dictionary and a Newspaper Corpus
Lee, Se-Hee ; Kim, Hark-Soo ;
The KIPS Transactions:PartB, volume 16B, issue 5, 2009, Pages 427~434
DOI : 10.3745/KIPSTB.2009.16B.5.427
With the rapid evolution of the Internet and mobile environments, text including spelling errors such as newly-coined words and abbreviated words are widely used. These spelling errors make it difficult to develop NLP (natural language processing) applications because they decrease the readability of texts. To resolve this problem, we propose a spelling error correction model using a spelling error correction dictionary and a newspaper corpus. The proposed model has the advantage that the cost of data construction are not high because it uses a newspaper corpus, which we can easily obtain, as a training corpus. In addition, the proposed model has an advantage that additional external modules such as a morphological analyzer and a word-spacing error correction system are not required because it uses a simple string matching method based on a correction dictionary. In the experiments with a newspaper corpus and a short message corpus collected from real mobile phones, the proposed model has been shown good performances (a miss-correction rate of 7.3%, a F1-measure of 97.3%, and a false positive rate of 1.1%) in the various evaluation measures.