• Journal of KIISE
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• v.44 no.1
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• pp.44-50
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• 2017

Pedestrian detection, an important component of autonomous driving and driving assistant system, has been extensively studied for many years. In particular, image based pedestrian detection methods such as Hierarchical classifier or HOG and, deep models such as ConvNet are well studied. The evaluation score has increased by the various methods. However, pedestrian detection requires high sensitivity to errors, since small error can lead to life or death problems. Consequently, further reduction in pedestrian detection error rate of autonomous systems is required. We proposed a new method to detect pedestrians and reduce the error rate by using the Faster R-CNN with new developed pedestrian training data sets. Finally, we compared the proposed method with the previous models, in order to show the improvement of our method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3C
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• pp.125-132
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• 2005

This paper describes a computer vision system based on active IR illumination for real-time gaze discrimination system. Unlike most of the existing gaze discrimination techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze discrimination system can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using generalized regression neural networks (GRNNs). With GRNNs, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Futhermore, the mapping function can generalize to other individuals not used in the training. To further improve the gaze estimation accuracy, we employ a reclassification scheme that deals with the classes that tend to be misclassified. This leads to a 10% improvement in classification error. The angular gaze accuracy is about 5°horizontally and 8°vertically. The effectiveness of our gaze tracker is demonstrated by experiments that involve gaze-contingent interactive graphic display.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.1
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• pp.38-46
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• 2010

This paper describes a computer vision system based on active IR illumination for real-time gaze discrimination system. Unlike most of the existing gaze discrimination techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze discrimination system can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using generalized regression neural networks (GRNNs). With GRNNs, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Furthermore, the mapping function can generalize to other individuals not used in the training. To further improve the gaze estimation accuracy, we employ a reclassification scheme that deals with the classes that tend to be misclassified. This leads to a 10% improvement in classification error. The angular gaze accuracy is about $5^{\circ}$horizontally and $8^{\circ}$vertically. The effectiveness of our gaze tracker is demonstrated by experiments that involve gaze-contingent interactive graphic display.

• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.130-138
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• 2014

This paper assessed the weights of attributes in creating transit malls. The aim of the creation was classified as travel demand management and urban revitalization. The attributes were grouped into four aspects, or 4As: attraction, amenity, accessibility, and activity. These dimensions represented land-use, urban design, transport, and socio-cultural characteristics, respectively. The analytical hierarchy process was applied to explore the weights. Accessibility(52.7%), attraction(25.6%), amenity(13.7%), and activity(8.0%) were the order of magnitude in weights for the purpose of travel demand management, while attraction(36.1%), accessibility(30.6%), amenity(17.7%), and activity(15.6%) were that of urban revitalization. The multi criteria analysis also showed different size of weights in the sub planning attributes. These results indicate that the aimin implementingtransit malls should be differentiated and highlight that the combined land-use and transport plan is essential for the successful development. Car accessibility and socio-cultural characteristics are also understood as the important factors.

• Journal of Broadcast Engineering
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• v.10 no.1 s.26
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• pp.103-118
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• 2005

Since the introduction of digital broadcasting, an additional advanced service called EPG has been brought to viewers. EPG (Electronic Program Guide) helps people select channels or programs. But existing user Interfaces for EPG are not convenient enough for the viewer. TV is the media anyone can access. Therefore, the 'look and feel' user interface is needed to guide the viewer to select their favorite programs without any difficulties. Generally, TV programs can be categorized by their attributes such as genre, broadcasting hours, and TV ratings. At the present moment, those attributes are not categorized systematically enough for easy program navigation. This paper presents how to organize the attributes of TV programs systematically and offers a user friendly interface to help the viewer access their favorite programs by specifying the values of the attributes in any order comfortable to them.

• Journal of Biomedical Engineering Research
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• v.29 no.6
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• pp.466-476
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• 2008

The more people use ambulatory electrocardiogram(ECG) for arrhythmia detection, the more researchers report the automatic classification algorithms. Most of the previous studies don't consider the un-balanced data distribution. Even in patients, there are much more normal beats than abnormal beats among the data from 24 hours. To solve this problem, the hierarchical classification using 21 features was adopted for arrhythmia abnormal beat detection. The features include R-R intervals and data to describe the morphology of the wave. To validate the algorithm, 44 non-pacemaker recordings from physionet were used. The hierarchical classification model with 2 stages on domain knowledge was constructed. Using our suggested method, we could improve the performance in abnormal beat classification from the conventional multi-class classification method. In conclusion, the domain knowledge based hierarchical classification is useful to the ECG beat classification with unbalanced data distribution.

• Journal of Advanced Navigation Technology
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• v.13 no.3
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• pp.459-465
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• 2009

Digital watermarking is a technique to insert a visually imperceptible information into an image so that the information can be extracted for the purposes of ownership verification or authentication. And watermarking techniques can be classified as either fragile or robust. Robust watermarks are useful for copyright and ownership assertion purposes. They cannot be easily removed and should resist common image manipulation procedures such as rotation, scaling, cropping, etc. On the other hand, fragile watermarks are easily corrupted by any image processing procedure, it can detect any change to an image as well as localizing the areas that have been changed. In this paper, we propose a fragile watermarking algorithm using a special hierarchical structure for integrity verification of image and detection of manipulated location. In the proposed method, the image to be watermarked is divided into blocks in a multi-level hierarchy and calculating block digital signatures in this hierarchy. The proposed method thwarts the cut-and-paste attack and the experimental results to demonstrate the effectiveness of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.322-329
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• 2005

This paper describes a computer vision system based on active IR illumination for real-time gaze discrimination system. Unlike most of the existing gaze discrimination techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze discrimination system can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using generalized regression neural networks (GRNNS). With GRNNS, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. furthermore, the mapping function can generalize to other individuals not used in the training. To further improve the gaze estimation accuracy, we employ a reclassification scheme that deals with the classes that tend to be misclassified. This leads to a 10$\%$ improvement in classification error. The angular gaze accuracy is about $5^{circ}$horizontally and $8^{circ}$vertically. The effectiveness of our gaze tracker is demonstrated by experiments that involve gaze-contingent interactive graphic display.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.941-951
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• 1999

Class components in a repository require exact information representation by reason of insufficiency of various visual information through search and extraction. In this paper, we have described syntax-analysis method and viewer facilities about class components. In the components analysis, we extracted class information which consists of class_names, methods, attributes, class inheritance relationship, and graphic information. viewer represents extracted class information and creates a new class. Also, it provides facilities of reuse, insertion, and deletion. Not only Viewer represents class hierarchy diagram, and shows detail information about each class, but also it creates new classes. In this paper, we implemented a Viewer using the components, inheritance, diagram information and process. And we enhanced understanding of programs through viewer, and supported prototype for class creation.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.113-118
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• 2002

This paper presents a cluster-based image retrieval method. It retrieves images from a related cluster after classifying images into clusters using RAGMD, a clustering technique. When images are retrieved, first they are retrieved not from the whole image database one by one but from the similar cluster, a similar small image group with a query image. So it gives us retrieval-time reduction, keeping almost the same precision with the exhaustive retrieval. In the experiment using an image database consisting of about 2,400 real images, it shows that the proposed method is about 18 times faster than 7he exhaustive method with almost same precision and it can retrieve more similar images which belong to the same class with a query image.