• Journal of Korea Multimedia Society
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• v.25 no.1
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• pp.124-134
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• 2022

Based on existing research, the psychological state of Chinese students has become a very significant issue that needs to be resolved. In addition to paying attention to the daily life and study of Chinese students, the psychological problems of Chinese students are also worthy of attention. At the same time, if the existing psychological problems are not resolved in time, serious consequences may result. Based on the ART(Attention Restoration Theory) theory, this article uses VR (Virtual Reality) content as a medium, uses 3D modeling software to build a healing scene that helps Chinese students improve their psychological and emotional state, and presents it in a VR device. To achieve the purpose of improving the psychological and emotional state of Chinese students. According to experimental tests, the VR recovery scene constructed by this method can help improve the psychological mood of Chinese international students who already have subliminal depression. The results of independent sample T-tests after data analysis experiments show that after the intervention of the experiment, the depression of the experimental group is significantly improved compared to the control group. It is proved that the method in this study is effective for the mentality and emotion of Chinese international students who have subliminal depression. There is a significant improvement effect.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.278-286
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• 2006

The purpose of this study was to investigate factors of film aesthetics, a core of creative power for works, and reference indicators to establish the successful model for works by analyzing Mise-en-scene through case works focused on domestic digital 3D short snimation that has developed consistently in recent years. As to the frame of analysis for Mise-en-scene, this study applied to the concept of triple articulation under discussion in U. Eco's film semiotics, but each factor is semes, figures, and cinemorphes. The case works were focused on by a film director Park Se Jong who was nominated for the Academy Award in 2005, and secured its objectivity.

• Spatial Information Research
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• v.18 no.3
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• pp.73-83
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• 2010

This study presents a method to segment an image, employing the statistics observed at each pixel location across sequential frame images. In the acquisition and analysis of spatial information, utilization of digital image processing technique has very important implications. Various image segmentation techniques have been presented to distinguish the area of digital images. In this study, based on the analysis of the spectroscopic characteristics of sequential frame images that had been previously researched, an image segmentation method was proposed by using the randomness occurring among a sequence of frame images for a same scene. First of all, we computed the mean and standard deviation values at each pixel and found reliable pixels to determine seed points using their standard deviation value. For segmenting an image into individual regions, we conducted region growing based on a T-test between reference and candidate sample sets. A comparative analysis was conducted to assure the performance of the proposed method with reference to a previous method. From a set of experimental results, it is confirmed that the proposed method using a sequence of frame images segments a scene better than a method using a single frame image.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.59-66
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• 2011

In this paper, we propose a face detection method based on color constancy and geometrical analysis. With the problem about the various colors of skin under scene illuminant, a color constancy method is applied to input images and geometrical analysis is used to detect face regions. At first, the candidates of face or hair are extracted from the image that a color constancy method is applied to, and are classified by some geometrical criterions. And then, face candidates which have some intersectional regions whose total is over a certain size, with hair candidates are selected as faces. Caltech Face DB was used to compare the performance of our method. Also, performance about scene illuminant was evaluated by images which have some illumination effects. The experiment results show that the proposed face detection method was applicable to various facial images because of high true-positive and low false-negative ration.

• Journal of Internet Computing and Services
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• v.12 no.2
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• pp.19-28
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• 2011

Recently, ubiquitous computing and related technologies is more and more growing concern about. Depending on the trend, the moving object recognition and tracking research have been required in order to meet the diverse needs of the user. In the location-based services, one of the most important issues in the indoor environment is to provide location-aware services. In this paper, the effective algorithm to help estimate the position of moving objects in an indoor environment is proposed. We propose an algorithm that combined the existing trilateration measurement and the improved measurement of environmental adaptation scene analysis. The proposed indoor location estimation algorithm use the trilateration measurement when we have enough anchor in the line-of-sight environment. Otherwise that use measurement of environmental adaptation scene analysis. Consequently, the proposed algorithm has been improved the localization accuracy of a moving object as well as was able to reduce complexity of the algorithm.

• Korean Journal of Clinical Laboratory Science
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• v.42 no.1
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• pp.22-31
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• 2010

The most common sources of biological trace material which are found in crime scene are the human bloodstains. Reliable identification in the forensic casework is important as it provides crucial insights into crime scene reconstruction and can thus contribute towards solving crimes. Blood-stains are routinely tested in forensic practise using various methods including the leucomalachite green (LMG) test, Kastle-Meyer phenolphthalein test, tetramethylbenzidine test, orthotolidine test, or the luminol chemoluminescence test with the latter cleaning attempts. All these presumptive thus indicative but not identifying tests take advantage of the peroxidase-like activity of the heme unit of the hemoglobin molecule in human blood. Therefore, false-positive results can be caused by the presence of strong oxidants, such as chlorine-containing detergents or by true peroxidases (e.g., from plants). In this study, composition for Gum guaiac was evaluated for the forensic identification of bloodstain and compared with the LMG. The sensitivity and specificity of the composition for Gum guaiac were examined more stable in bloodstain. The positive of Composition for Gum guaiac shown even with the 100,000-fold diluted bloodstain, which was no difference in comparison with LMG test. It was shown that composition for Gum guaiac was very stable to resist boiling for 20 minutes and the effect of bacteria did not affect the genetic analysis as well. The above result of the crime scene investigation, composition for Gum guaiac is easily expected to help identifying bloodstain in the evidences.

• Journal of Broadcast Engineering
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• v.11 no.1 s.30
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• pp.28-41
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• 2006

Due to the rapid development of multimedia appliances, the increasing amount of multimedia data enforces the development of automatic video analysis techniques. In this paper, a method of ToC generation is proposed for educational video contents. The proposed method consists of two parts: scene segmentation followed by scene annotation. First, video sequence is divided into scenes by the proposed scene segmentation algorithm utilizing the characteristics of educational video. Then each shot in the scene is annotated in terms of scene type, existence of enclosed caption and main speaker of the shot. The ToC generated by the proposed method represents the structure of a video by the hierarchy of scenes and shots and gives description of each scene and shot by extracted features. Hence the generated ToC can help users to perceive the content of a video at a glance and. to access a desired position of a video easily. Also, the generated ToC automatically by the system can be further edited manually for the refinement to effectively reduce the required time achieving more detailed description of the video content. The experimental result showed that the proposed method can generate ToC for educational video with high accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2427-2432
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• 2014

Color-$X^2$ is used as a method for scene change detection. It extracts a violent scene in an elevator and then could be used for real-time surveillance of criminal acts. The scene could be also used to secure after-discovered evidences and to prove analysis processes. Video Forensic is defined as a research on various methods to efficiently analyze evidences upon crime-related visual images in the field of digital forensic. The method to use differences of color-histogram detects the difference values of histogram for RGB color from two frames respectively. Our paper uses Color-$X^2$ histogram that is composed of merits of color histogram and ones of $X^2$ histogram, in order to efficiently extract violent scenes in elevator. Also, we use a threshold so as to find out key frame, by use of existing Color-$X^2$ histogram. To increase the probability that discerns whether a real violent scene or not, we take advantage of statistical judgments with 20 sample visual images.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.484-491
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• 2015

Aerial scene is greatly increased by the introduction and supply of the image due to the growth of digital optical imaging technology and development of the UAV. It has been used as the extraction of ground properties, classification, change detection, image fusion and mapping based on the aerial image. In particular, in the image analysis and utilization of deep learning algorithm it has shown a new paradigm to overcome the limitation of the field of pattern recognition. This paper presents the possibility to apply a more wide range and various fields through the segmentation and classification of aerial scene based on the Deep learning(ConvNet). We build 4-classes image database consists of Road, Building, Yard, Forest total 3000. Each of the classes has a certain pattern, the results with feature vector map come out differently. Our system consists of feature extraction, classification and training. Feature extraction is built up of two layers based on ConvNet. And then, it is classified by using the Multilayer perceptron and Logistic regression, the algorithm as a classification process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.3036-3044
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• 2010

With the rapid growth of video data service, demand to provide advertisements or additional information with regard to a particular video scene is increasing. However, the direct use of automated visual analysis or speech recognition on videos virtually has limitations with current level of technology; the metadata of video such as title, category information, or summary does not reflect the content of continuously changing scenes. This work presents a new video contextual advertising system that serves relevant advertisements on a given scene by leveraging the scene's situation information inferred from video scripts. Experimental results show that the use of situation information extracted from scripts leads to better performance and display of more relevant advertisements to the user.