• IEMEK Journal of Embedded Systems and Applications
• /
• v.19 no.1
• /
• pp.27-32
• /
• 2024

Recently, there has been a growing interest in integrating physical toys into video gaming within the game content business. This paper introduces a novel method that leverages low-cost camera as an alternative to using sensor attachments to meet this rising demand. We address the limitations associated with low-cost cameras and propose an optical design tailored to the specific environment of model car recognition. We overcome the inherent limitations of low-cost cameras by proposing an optical design specifically tailored for model car recognition. This approach primarily focuses on recognizing the underside of the car and addresses the challenges associated with this particular perspective. Our method employs a transfer learning model that is specifically trained for this task. We have achieved a 100% recognition rate, highlighting the importance of collecting data under various camera exposures. This paper serves as a valuable case study for incorporating low-cost cameras into vision systems.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.2
• /
• pp.105-111
• /
• 2008

Various visualizing methods have been proposed according to the input and output types. To show complex and large-scale raw data and information. LOD and special region scale method have been used for them. In this paper, I propose level scale interface for dynamic and interactive controlling large scale data such as bio-data. The method has not only advantage of LOD and special region scale but also dynamic and real-time processing. In addition, the method supports elaborate control from large scale to small one for visualization on a region in detail. Proposed method was adopted for genome relationship visualization tool and showed reasonable control method.

• The Journal of Information Systems
• /
• v.29 no.4
• /
• pp.45-56
• /
• 2020

Purpose The purpose of this study is to present the direction of efficient e-learning education through the importance and satisfaction survey of learners of non-face-to-face video lectures. Therefore, by grasping the degree of satisfaction of the importance ratio through the IPA analysis method, we try to present improvement measures for insufficient education methods. Design/methodology/approach For IPA analysis, we conducted an online survey of four universities and analyzed 154 samples. The analysis method used SPSS, and through the wordcloud analysis method of R, the suggestions for the non-face-to-face lecture method felt by learners were analyzed to derive implications for improving the quality of education. Findings As a result of the overall satisfaction survey for the entire non-face-to-face class, the factors with the greatest dissatisfaction are listed as follows. Complaints about the adequacy of learning materials and activities (quiz, discussion, assignments, etc.), Complaints about how to use the produced content, and complaints about announcements about class management (lecture schedule, lecture method) were identified in order. The factors of dissatisfaction were clear in the non-face-to-face class where interactive communication was impossible or insufficient. In addition to the lack of quick Q&A, there seems to have been a phenomenon of some neglect.

• Journal of the Korea Computer Graphics Society
• /
• v.8 no.2
• /
• pp.15-22
• /
• 2002

Image segmentation methods partition an image into meaningful regions. For image composition and analysis, it is desirable for the partitioned regions to represent meaningful objects in terms of human perception and manipulation. Despite the recent progress in image understanding, however, most of the segmentation methods mainly employ low-level image features and it is still highly challenging to automatically segment an image based on high-level meaning suitable for human interpretation. The concept of HCI (Human Computer Interaction) can be applied to operator-assisted image segmentation in a manner that a human operator provides guidance to automatic image processing by interactively supplying critical information about object boundaries. Intelligent Scissors and Snakes have demonstrated the effectiveness of human-assisted segmentation [2] [1]. This paper presents a method for interactive image segmentation for more efficient and effective detection and tracking of object boundaries. The presented method is partly based on the concept of Intelligent Scissors, but employs the well-established Canny edge detector for stable edge detection. It also uses "sewing method" for including weak edges in object boundaries, and 5-direction search to promote more efficient and stable linking of neighboring edges than the previous methods.

• Journal of Korea Game Society
• /
• v.10 no.4
• /
• pp.81-90
• /
• 2010

In this paper, an efficient method is proposed to produce photorealistic images of woven fabrics without empirical data such as the measured BRDFs(bidirectional reflectance distribution functions). The proposed method is applicable both to ray tracer based offline renderers and to realtime applications such as games. The proposed method models the reflectance properties of woven fabric with alternating anisotropy and deformed MDF(microfacet distribution function). The procedural modeling of the yarn structure effectively and efficiently reproduces plausible rendering of woven fabric. The experimental results show the proposed method can be successfully applied to photorealistic rendering of diverse woven fabric materials even in interactive applications.

• Mass Spectrometry Letters
• /
• v.3 no.3
• /
• pp.78-81
• /
• 2012

The hydrophobic hydrocarbon chain and the polar sulfate group confer surfactant properties and enable them to be used as anionic surfactants. Anionic surfactants (AS) are known for their adverse impact on environment, particularly on aquatic ecosystem. In the present study a fast, sensitive and selective method for the determination and subsequent quantification of six anionic surfactants was developed using hydrophilic interactive liquid chromatography (HILIC) coupled to a electrospray ionization (ESI) mass spectrometer (MS), in the concentration range 15-20 ${\mu}g/L$. The capability of the method was established using regression analysis and ANOVA. The method performance was evaluated by analyzing real time surface water spiked with 1-dodecyl hydrogen sulfate at 15 ${\mu}g/L$. Combined efficiency of solid phase extraction and MS detection established recovery of 89% in presence of natural matrix. These results point out that HILIC coupled to multistage MS procedures can be a powerful technique for environmental applications concerning the screening of polar contaminants.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.290-293
• /
• 2009

In this paper, we propose a method to estimate pointing region in real-world from images of cameras. In general, arm-pointing gesture encodes a direction which extends from user's fingertip to target point. In the proposed work, we assume that the pointing ray can be approximated to a straight line which passes through user's face and fingertip. Therefore, the proposed method extracts two end points for the estimation of pointing direction; one from the user's face and another from the user's fingertip region. Then, the pointing direction and its target region are estimated based on the 2D-3D projective mapping between camera images and real-world scene. In order to demonstrate an application of the proposed method, we constructed an ICGS (interactive cinema guiding system) which employs two CCD cameras and a monitor. The accuracy and robustness of the proposed method are also verified on the experimental results of several real video sequences.

• ETRI Journal
• /
• v.37 no.4
• /
• pp.766-771
• /
• 2015

Robust motion estimation for human-computer interactions played an important role in a novel method of interaction with electronic devices. Existing pose estimation using a monocular camera employs either ego-motion or exo-motion, both of which are not sufficiently accurate for estimating fine motion due to the motion ambiguity of rotation and translation. This paper presents a hybrid vision-based pose estimation method for fine-motion estimation that is specifically capable of extracting human body motion accurately. The method uses an ego-camera attached to a point of interest and exo-cameras located in the immediate surroundings of the point of interest. The exo-cameras can easily track the exact position of the point of interest by triangulation. Once the position is given, the ego-camera can accurately obtain the point of interest's orientation. In this way, any ambiguity between rotation and translation is eliminated and the exact motion of a target point (that is, ego-camera) can then be obtained. The proposed method is expected to provide a practical solution for robustly estimating fine motion in a non-contact manner, such as in interactive games that are designed for special purposes (for example, remote rehabilitation care systems).

• Journal of Power Electronics
• /
• v.15 no.4
• /
• pp.1066-1073
• /
• 2015

This paper proposes a control strategy based on the frequency detection method, comprising a current control and a feed-forward voltage control loop, is proposed for grid-interactive power conditioning systems (PCS). For continuous provision of power to critical loads, PCS should be able to check grid outages instantaneously. Hence, proposed in the present paper are a frequency detection method for detecting abnormal grid conditions and a controller, which consists of a current controller and a feedforward voltage controller, for different operation modes. The frequency detection method can detect abnormal grid conditions accurately and quickly. The controller which has current and voltage control loops rapidly helps in load voltage regulation when grid fault occurs by changing reference and control modes. The proposed seamless transfer control strategy is confirmed by experimental results.

• ETRI Journal
• /
• v.43 no.5
• /
• pp.812-824
• /
• 2021

Recently, with an increase in Internet usage, users of online social networks (OSNs) have increased. Consequently, privacy leakage has become more serious. However, few studies have investigated the difference between privacy and actual behaviors. In particular, users' desire to change their privacy status is not supported by their privacy literacy. Presenting an accurate measurement of users' privacy status can cultivate the privacy literacy of users. However, the highly interactive nature of interpersonal communication on OSNs has promoted privacy to be viewed as a communal issue. As a large number of redundant users on social networks are unrelated to the user's privacy, existing algorithms are no longer applicable. To solve this problem, we propose a structural similarity measurement method suitable for the characteristics of social networks. The proposed method excludes redundant users and combines the attribute information to measure the privacy status of users. Using this approach, users can intuitively recognize their privacy status on OSNs. Experiments using real data show that our method can effectively and accurately help users improve their privacy disclosures.