• 한국HCI학회:학술대회논문집
• /
• 2008.02a
• /
• pp.540-546
• /
• 2008

In the near future, robots should be able to understand human's emotional states and exhibit appropriate behaviors accordingly. In Human-Human Interaction, the 93% consist of the speaker's nonverbal communicative behavior. Bodily movements provide information of the quantity of emotion. Latest personal robots can interact with human using multi-modality such as facial expression, gesture, LED, sound, sensors and so on. However, a posture needs a position and an orientation only and in facial expression or gesture, movements are involved. Verbal, vocal, musical, color expressions need time information. Because synchronization among multi-modalities is a key problem, emotion expression needs a systematic approach. On the other hand, at low intensity of surprise, the face could be expressed but the gesture could not be expressed because a gesture is not linear. It is need to decide the emotional boundaries for effective robot behavior generation and synchronization with another expressible method. If it is so, how can we define emotional boundaries? And how can multi-modality be synchronized each other?

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.25 no.1
• /
• pp.295-318
• /
• 2014

The purpose of this study is to analyze the intellectual structure of reading studies by using Co-Word Analysis based on the mixed weight in which the level of academic journals and the position of keywords are calculated. To achieve it, 838 academic articles relating to reading studies from KCI during the period from 2003 to 2012 were retrieved and 56 keywords were extracted. The results of clustering analysis, MDS, network analysis are that the network based on the mixed weight has a better performance in above three methods and reading studies can be divided into 4 bigger divisions and 11 subdivisions. Finally, the result of document analysis shows reading studies changes its research tendency from theoretical studies to empirical studies.

• The KIPS Transactions:PartB
• /
• v.9B no.3
• /
• pp.343-350
• /
• 2002

A scene change detection which involves finding a cut between two consecutive shots is an important step for video indexing and retrieval. This paper proposes an algorithm for fast and accurate detection of abrupt scene changes in an MPEG compressed domain with minimal decoding requirements arid computational effort. The proposed method compares two successive DC images of I-frames for finding the GOP (group of picture) which contain a scene change and uses macroblock-coded type information contained in B-frames to detect the exact frame where the scene change occurred. The experiment results demonstrate that the proposed algorithm has better detection performance, such as precision and recall rate, than the existing method using all DC images. The algorithm has the advantage of speed, simplicity and accuracy. In addition, it requires less amount of storage.

• Journal of the Korea Computer Graphics Society
• /
• v.12 no.4
• /
• pp.7-15
• /
• 2006

The ultimate objective of painterly rendering is to express an inputted image as if it is hand drawn. The factors to express this painterly effect are thickness of the brush, direction, texture and the establishment of criteria judging if the produced brush will be drawn on to the canvas. In this paper, the algorithm using density of the edges in determining the criteria whether the brush will be drawn onto the canvas is proposed. Density of edges refers to the quantity of edge in the specific area. And uses the method of finding the location of the brush to be drawn as a unit of dynamic grid as well as expressing consistent directional through direction interpolation. Also, the texture is expressed using various textured brushes. Considering density of edges,We can express detailed area and abstract area. And it result in more human effect of oil painting.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2003.05a
• /
• pp.165-170
• /
• 2003

This paper presents an integrated approach to unconstrained face recognition in arbitrary scenes. The front end of the system comprises of a scale and pose tolerant face detector. Scale normalization is achieved through novel combination of a skin color segmentation and log-polar mapping procedure. Principal component analysis is used with the multi-view approach proposed in[10] to handle the pose variations. For a given color input image, the detector encloses a face in a complex scene within a circular boundary and indicates the position of the nose. Next, for recognition, a radial grid mapping centered on the nose yields a feature vector within the circular boundary. As the width of the color segmented region provides an estimated size for the face, the extracted feature vector is scale normalized by the estimated size. The feature vector is input to a trained neural network classifier for face identification. The system was evaluated using a database of 20 person's faces with varying scale and pose obtained on different complex backgrounds. The performance of the face recognizer was also quite good except for sensitivity to small scale face images. The integrated system achieved average recognition rates of 87% to 92%.

• Journal of KIISE
• /
• v.42 no.3
• /
• pp.390-398
• /
• 2015

Spatial web objects refer to web documents that contain geographic information. Recently, services that create spatial web objects have increased greatly because of the advancements in devices such as smartphones. For services such as Twitter or Facebook, simple texts posted by users is stored along with information about the post's location. To search for such spatial web objects, a method that uses spatial information and text information simultaneously is required. Conventional spatial web object search methods mostly use R-tree and inverted file methods. However, these methods have a disadvantage of requiring a large volume of space when building indices. Furthermore, such methods are efficient for searching with many keywords but are inefficient for searching with a few keywords.. In this paper, we propose a spatial web object search method that uses a quad-tree and a patricia-trie. We show that the proposed technique is more effective than existing ones in searching with a small number of keywords. Furthermore, we show through an experiment that the space required by the proposed technique is much smaller than that required by existing ones.

• Journal of Broadcast Engineering
• /
• v.21 no.6
• /
• pp.965-976
• /
• 2016

Recently studies about audio-visual immersion are being carried out due to development of digital video but studies analysing quantitatively the content or climax of video has not carried out. The paper is analysed quantitatively by using shot size, camera angle, camera direction and camera position, objective & subjective which is general component of video expression. We can see the climax effects in the video destroying the principles because there is a rule when they use the component. This thesis analyses shot-list based on video expression in existing movies therefore it can analyse quantitatively several method commonly used in order to make the climax. These suggesting method that can find the part of climax based on analysis of shot-list can be used when you search the specific part of video like long movie or when you search the genre of the movie or when you index the genre. Also it can be very effective in various information services companies offering climax movie which is searched.

• Journal of Korea Technology Innovation Society
• /
• v.17 no.2
• /
• pp.334-354
• /
• 2014

This study aims to analyze the research trend of Korean medicine based on social network analysis. To do this, a dataset has been collected from KCI (Korea Citation Index) database. According to the results, we have identify the longitudinal trend of the number of papers, journals, organizations and key words in this field. Moreover, based on the nodes' centrality of co-author network, we have found a core journal (i.e. Korean Journal of Oriental Physiology and Pathology), a hub institution (i.e. Kyunghee university) and two main key words (i.e. anti-oxidation and acupuncture) in the research network. In conclusion, integrating field experts' tacit knowledge in Korean medicine studies with the results of the explicit social network analysis on the research trend, we put forward further policy implications with regard to R&D strategies in this field.

• Journal of Korean Ophthalmic Optics Society
• /
• v.18 no.2
• /
• pp.187-191
• /
• 2013

Purpose: This study was done to understand the visual system of bat by analyzing the distribution of middle/long (ML) opsin cone photoreceptors in the retina of the greater horseshoe bat. Methods: Experiments have been performed by standard immunocytochemical techniques on retina of the greater horseshoe bat Rhinolophus ferrumequinum. Results: The estimated numbers of ML cones were $27,336{\pm}2,130$ cells and the mean density of them was $7,854{\pm}268cells/mm^2$ among the four retinas. S opsin was appeared a little immunoreactivity in the outer segments of outer nuclear layer of cones. Conclusions: From the well organized spatial distributions of ML opsin and the immunoreactivity of S opsin in the retinas, the greater horseshoe bats have the functions not only reacting in the photopic vision but being able to distinguish the colors.

• Korean Journal of Cognitive Science
• /
• v.25 no.1
• /
• pp.51-71
• /
• 2014

This paper presents an image enhancement method in real road traffic scenes. The images captured by the camera on the car cannot keep the color constancy as illumination or weather changes. In the real environment, these problems are more worse at back light conditions and at night that make more difficult to the applications of the vision-based intelligent vehicles. Using the existing image enhancement methods without considering the position and intensity of the light source and their geometric relations the image quality can even be deteriorated. Thus, this paper presents a fast and effective method for image enhancement resembling human cognitive system which consists of 1) image preprocessing, 2) color-contrast evaluation, 3) alpha blending of over/under estimated image and preprocessed image. An input image is first preprocessed by gamma correction, and then enhanced by an Automatic Color Enhancement(ACE) method. Finally, the preprocessed image and the ACE image are blended to improve image visibility. The proposed method shows drastically enhanced results visually, and improves the performance in traffic sign detection of the vision based intelligent vehicle applications.