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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 14B, Issue 7 - Dec 2007
Volume 14B, Issue 6 - Oct 2007
Volume 14B, Issue 5 - Oct 2007
Volume 14B, Issue 4 - Aug 2007
Volume 14B, Issue 3 - Jun 2007
Volume 14B, Issue 2 - Apr 2007
Volume 14B, Issue 1 - Feb 2007
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Regularization Parameter Determination for Optical Flow Estimation using L-curve
Kim, Jong-Dae ; Kim, Jong-Won ;
The KIPS Transactions:PartB, volume 14B, issue 4, 2007, Pages 241~248
DOI : 10.3745/KIPSTB.2007.14-B.4.241
An L-curve corner detection method is proposed for the determination of the regularization parameter in optical flow estimation. The method locates the positive peak whose curvature difference from the just right-hand negative valley is the maximum in the curvature plot of the L-curve. while the existing curvature-method simply finds the maximum in the plot. Experimental results show that RMSE of the estimated optical flow is greater only by 0.02 pixels-per-frame than the least in the average sense. The proposed method is also compared with an existing curvature-method and the adaptive pruning method, resulting in the optical flow estimation closest to the least RMSE.
Object Detection Method on Vision Robot using Sensor Fusion
Kim, Sang-Hoon ;
The KIPS Transactions:PartB, volume 14B, issue 4, 2007, Pages 249~254
DOI : 10.3745/KIPSTB.2007.14-B.4.249
A mobile robot with various types of sensors and wireless camera is introduced. We show this mobile robot can detect objects well by combining the results of active sensors and image processing algorithm. First, to detect objects, active sensors such as infrared rays sensors and supersonic waves sensors are employed together and calculates the distance in real time between the object and the robot using sensor's output. The difference between the measured value and calculated value is less than 5%. We focus on how to detect a object region well using image processing algorithm because it gives robots the ability of working for human. This paper suggests effective visual detecting system for moving objects with specified color and motion information. The proposed method includes the object extraction and definition process which uses color transformation and AWUPC computation to decide the existence of moving object. Shape information and signature algorithm are used to segment the objects from background regardless of shape changes. We add weighing values to each results from sensors and the camera. Final results are combined to only one value which represents the probability of an object in the limited distance. Sensor fusion technique improves the detection rate at least 7% higher than the technique using individual sensor.
Face Region Detection using a Color Union Model and The Levenberg-Marquadt Algorithm
Kim, Jin-Ok ;
The KIPS Transactions:PartB, volume 14B, issue 4, 2007, Pages 255~262
DOI : 10.3745/KIPSTB.2007.14-B.4.255
This paper proposes an enhanced skin color-based detection method to find a region of human face in color images. The proposed detection method combines three color spaces, RGB,
, YIQ and builds color union histograms of luminance and chrominance components respectively. Combined color union histograms are then fed in to the back-propagation neural network for training and Levenberg-Marquadt algorithm is applied to the iteration process of training. Proposed method with Levenberg-Marquadt algorithm applied to training process of neural network contributes to solve a local minimum problem of back-propagation neural network, one of common methods of training for face detection, and lead to make lower a detection error rate. Further, proposed color-based detection method using combined color union histograms which give emphasis to chrominance components divided from luminance components inputs more confident values at the neural network and shows higher detection accuracy in comparison to the histogram of single color space. The experiments show that these approaches perform a good capability for face region detection, and these are robust to illumination conditions.
Skeleton Tree for Shape-Based Image Retrieval
Park, Jong-Seung ;
The KIPS Transactions:PartB, volume 14B, issue 4, 2007, Pages 263~272
DOI : 10.3745/KIPSTB.2007.14-B.4.263
This paper proposes a skeleton-based hierarchical shape description scheme, called a skeleton tree, for accurate shape-based image retrieval. A skeleton tree represents an object shape as a hierarchical tree where high-level nodes describe parts of coarse trunk regions and low-level nodes describe fine details of boundary regions. Each node refines the shape of its parent node. Most of the noise disturbances are limited to bottom level nodes and the boundary noise is reduced by decreasing weights on the bottom levels. The similarity of two skeleton trees is computed by considering the best match of a skeleton tree to a sub-tree of another skeleton tree. The proposed method uses a hybrid similarity measure by employing both Fourier descriptors and moment invariants in computing the similarity of two skeleton trees. Several experimental results are presented demonstrating the validity of the skeleton tree scheme for the shape description and indexing.
' Toolkit for Interactive Sound in Virtual Environment
Nam, Yang-Hee ; Sung, Suk-Jeong ;
The KIPS Transactions:PartB, volume 14B, issue 4, 2007, Pages 273~280
DOI : 10.3745/KIPSTB.2007.14-B.4.273
This paper presents a new 3D sound toolkit called
that consists of pre-processing tool for environment simplification preserving sound effect and 3D sound API for real-time rendering. It is designed so that it can allow users to interact with complex 3D virtual environments by audio-visual modalities.
toolkit would serve two different types of users: high-level programmers who need an easy-to-use sound API for developing realistic 3D audio-visually rendered applications, and the researchers in 3D sound field who need to experiment with or develop new algorithms while not wanting to re-write all the required code from scratch. An interactive virtual environment application is created with the sound engine constructed using
toolkit, and it shows the real-time audio-visual rendering performance and the applicability of proposed
for building interactive applications with complex 3D environments.
An Intelligent Context-Awareness Middleware for Service Adaptation based on Fuzzy Inference
Ahn, Hyo-In ; Yoon, Seok-Hwan ; Yoon, Yong-Ik ;
The KIPS Transactions:PartB, volume 14B, issue 4, 2007, Pages 281~286
DOI : 10.3745/KIPSTB.2007.14-B.4.281
This paper proposes an intelligent context awareness middleware(ICAM) for Ubiquitous Computing Environment. In this paper we have researched about the context awareness middleware. The ICAM model is based on ontology that efficiently manages analyses and learns about various context information and can provide intelligent services that satisfy the human requirements. Therefore, various intelligent services will improve user's life environment. We also describe the current implementation of the ICAM for service adaptation based on fuzzy inference that help applications to adapt their ubiquitous computing environments according to rapidly changing. For this, after defining the requirements specifications of ICAM, we have researched the inferred processes for the higher level of context awareness. The Fuzzy Theory has been used in process of inferences, and showed constructing the model through the service process. Also, the proposed fuzzy inferences has been applied to smart Jacky, and after inferring the fuzzy values according to the change of temperature, showed the adaptability of Smart Jacky according to the change of surroundings like temperature as showing the optimal value of status.
Improved Focused Sampling for Class Imbalance Problem
Kim, Man-Sun ; Yang, Hyung-Jeong ; Kim, Soo-Hyung ; Cheah, Wooi Ping ;
The KIPS Transactions:PartB, volume 14B, issue 4, 2007, Pages 287~294
DOI : 10.3745/KIPSTB.2007.14-B.4.287
Many classification algorithms for real world data suffer from a data class imbalance problem. To solve this problem, various methods have been proposed such as altering the training balance and designing better sampling strategies. The previous methods are not satisfy in the distribution of the input data and the constraint. In this paper, we propose a focused sampling method which is more superior than previous methods. To solve the problem, we must select some useful data set from all training sets. To get useful data set, the proposed method devide the region according to scores which are computed based on the distribution of SOM over the input data. The scores are sorted in ascending order. They represent the distribution or the input data, which may in turn represent the characteristics or the whole data. A new training dataset is obtained by eliminating unuseful data which are located in the region between an upper bound and a lower bound. The proposed method gives a better or at least similar performance compare to classification accuracy of previous approaches. Besides, it also gives several benefits : ratio reduction of class imbalance; size reduction of training sets; prevention of over-fitting. The proposed method has been tested with kNN classifier. An experimental result in ecoli data set shows that this method achieves the precision up to 2.27 times than the other methods.
A Semantic-Based Information Filling System Using Ontology
Min, Young-Kun ; Kim, In-Su ; Lee, Bog-Ju ;
The KIPS Transactions:PartB, volume 14B, issue 4, 2007, Pages 295~302
DOI : 10.3745/KIPSTB.2007.14-B.4.295
It is very iterative and complicated work to enter the personal information every time one fills the form-based resume or one joins the new membership page on the internet. Although there are some systems that have the personal information on the computer and fill the membership page automatically, their accuracies are not often satisfactory in that the fields and their values do not match exactly. The research proposes and implements a system that has user's information on the computer and reasons and fills the information automatically that a membership web page(target page) requests using the personal information ontology. During the reasoning process, the target page is analyzed to extract the requested fields. Then the requested field names are converted to the standard field names using synonym ontology. The converted requested fields find the appropriate level in the personal information ontology using ontology match making to generate the final field value. The system not only finds the similar fields but also generates the exact field values by reasoning on the information ontology hierarchy. By experimenting with several membership pages on the web, the system showed higher accuracy over the existing systems. The system can be easily applicable to the cases where one iteratively fills the same information such as resume form.
Ensemble Learning of Region Based Classifiers
Choi, Sung-Ha ; Lee, Byung-Woo ; Yang, Ji-Hoon ;
The KIPS Transactions:PartB, volume 14B, issue 4, 2007, Pages 303~310
DOI : 10.3745/KIPSTB.2007.14-B.4.303
In machine learning, the ensemble classifier that is a set of classifiers have been introduced for higher accuracy than individual classifiers. We propose a new ensemble learning method that employs a set of region based classifiers. To show the performance of the proposed method. we compared its performance with that of bagging and boosting, which ard existing ensemble methods. Since the distribution of data can be different in different regions in the feature space, we split the data and generate classifiers based on each region and apply a weighted voting among the classifiers. We used 11 data sets from the UCI Machine Learning Repository to compare the performance of our new ensemble method with that of individual classifiers as well as existing ensemble methods such as bagging and boosting. As a result, we found that our method produced improved performance, particularly when the base learner is Naive Bayes or SVM.
3D Facial Animation with Head Motion Estimation and Facial Expression Cloning
Kwon, Oh-Ryun ; Chun, Jun-Chul ;
The KIPS Transactions:PartB, volume 14B, issue 4, 2007, Pages 311~320
DOI : 10.3745/KIPSTB.2007.14-B.4.311
This paper presents vision-based 3D facial expression animation technique and system which provide the robust 3D head pose estimation and real-time facial expression control. Many researches of 3D face animation have been done for the facial expression control itself rather than focusing on 3D head motion tracking. However, the head motion tracking is one of critical issues to be solved for developing realistic facial animation. In this research, we developed an integrated animation system that includes 3D head motion tracking and facial expression control at the same time. The proposed system consists of three major phases: face detection, 3D head motion tracking, and facial expression control. For face detection, with the non-parametric HT skin color model and template matching, we can detect the facial region efficiently from video frame. For 3D head motion tracking, we exploit the cylindrical head model that is projected to the initial head motion template. Given an initial reference template of the face image and the corresponding head motion, the cylindrical head model is created and the foil head motion is traced based on the optical flow method. For the facial expression cloning we utilize the feature-based method, The major facial feature points are detected by the geometry of information of the face with template matching and traced by optical flow. Since the locations of varying feature points are composed of head motion and facial expression information, the animation parameters which describe the variation of the facial features are acquired from geometrically transformed frontal head pose image. Finally, the facial expression cloning is done by two fitting process. The control points of the 3D model are varied applying the animation parameters to the face model, and the non-feature points around the control points are changed by use of Radial Basis Function(RBF). From the experiment, we can prove that the developed vision-based animation system can create realistic facial animation with robust head pose estimation and facial variation from input video image.