• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.4
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• pp.414-420
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• 2018

The digital convergence looking for new ways to engage visitors by superimposing virtual content on projection over the real world captured media contents. This paper propose the Light ID based interactive 3D immersive exhibition things view using HMD AR technology. This approach does not required to add any additional infrastructure to be built-in to enable service and uses the installed Lighting or displays devices in the exhibit area. In this approach, the Light ID can be used as a Location Identifier and communication medium to access the content unlike the QR Tag which supports provide the download information through web interface. This utilize the advantages of camera based optical wireless communication (OWC) to receive the media content on smart device to deliver immersive 3D content visualization using AR. The proposed exhibition method is emulated on GALAXY S8 smart phone and the visual performance is evaluated for Jeonju Hanok Village. The experimental results shows that the proposed method can give immersive 3D view for exhibit things in real-time.

• The Journal of the Korea Contents Association
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• v.13 no.1
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• pp.30-39
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• 2013

In recent years, with the development of devices to collect multimedia data such as small CMOS camera sensor and micro phone, studies on wireless multimedia sensor network technologies and their applications that extend the existing wireless sensor network technologies have been actively done. In such applications, various basic schemes such as the processing, storage, and transmission of multimedia data are required. Especially, a security for real world environments is essential. In this paper, in order to defend the sniffing attack in various hacking techniques, we propose a multipath routing scheme for physically avoiding the data transmission path from the risk factors. Our proposed scheme establishes the DEFCON of the sensor nodes that are geographically close to risk factors and the priorities according to the importance of the data. Our proposed scheme performs risk factor detour multipath routing through a safe path considering the DEFCON and data priority. Our experimental results show that although our proposed scheme takes the transmission delay time by about 5% over the existing scheme, it reduces the eavesdropping rate that can attack and intercept data by the risk factor by about 18%.

• Korean Institute of Interior Design Journal
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• v.26 no.1
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• pp.33-42
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• 2017

Interior design especially the design developments for commercial spaces should ensure the economy of spaces. This is the marketing for space. It is necessary to understand the design elements of commercial space for the efficient using of digital media of space marketing. In this research decided to design application schemes for shopping mall by searching fashion shopping behaviors of users with persona-base scenario approach. Collected the information of users behavior base on case analysis of advance research to make personas. And develop scenario base personas for knowing the needs of users. And then made 4 schemes as the solution. Scheme 1. Customers can get the information and communication with the staff through with media screen in one room of shopping mall. The data of customers can be recorded for providing information or product recommendation personality. Forecast to preferred by group trip or customers that don't like walking around in shopping mall. Scheme 2. Install a media screen at entrance of a store in shopping mall and show special effect to raise customers' attention who walk through from the front of the store. Through with this customers will stay for long time and raise curiosity to get in the store. And the media screen also provide information of store and products. Scheme 3. Customers can get the information of products with using smart phone to scan QR cord in labels of products and record. Customers can finish whole shopping behaviors without the help of store staff. And can make buying decision even have left shopping mall as a online mode. Scheme 4. Store managers can record the products and the environment of store with 360 camera and update to website. Then customers can browse the virtual space with VR glasses. That make customers can have the real shopping experience without being in the store. In this study, have presented schemes of digital media in commercial space. But there are various of commercial space. In this study was presented schemes for shopping mall by searching fashion shopping behaviors of users. And look forward the researches about specific space setting and other type of commercial space for space development.

• Journal of Broadcast Engineering
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• v.27 no.2
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• pp.228-239
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• 2022

In this paper, we propose an unmanned vehicle scratch detection deep learning model for car sharing services. Conventional scratch detection models consist of two steps: 1) a deep learning module for scratch detection of images before and after rental, 2) a manual matching process for finding newly generated scratches. In order to build a fully automatic scratch detection model, we propose a one-step unmanned scratch detection deep learning model. The proposed model is implemented by applying transfer learning and fine-tuning to the deep learning model that detects changes in satellite images. In the proposed car sharing service, specular reflection greatly affects the scratch detection performance since the brightness of the gloss-treated automobile surface is anisotropic and a non-expert user takes a picture with a general camera. In order to reduce detection errors caused by specular reflected light, we propose a preprocessing process for removing specular reflection components. For data taken by mobile phone cameras, the proposed system can provide high matching performance subjectively and objectively. The scores for change detection metrics such as precision, recall, F1, and kappa are 67.90%, 74.56%, 71.08%, and 70.18%, respectively.

• Journal of the Korea Computer Graphics Society
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• v.28 no.3
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• pp.79-89
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• 2022

With the popularity and the advanced graphics hardware technology of mobile devices, various mobile applications that help children with physical activities have been studied. This paper presents SandUp, a mobile application that guides the play of building sand castles using artificial intelligence and augmented reality(AR) technology. In the process of building the sandcastle, children can interactively explore the target virtual sandcastle through the smartphone display using AR technology. In addition, to help children complete the sandcastle, SandUp informs the sand shape and task required step by step and provides visual and auditory feedback while recognizing progress in real-time using the phone's camera and deep learning classification. We prototyped our SandUp app using Flutter and TensorFlow Lite. To evaluate the usability and effectiveness of the proposed SandUp, we conducted a questionnaire survey on 50 adults and a user study on 20 children aged 4~7 years. The survey results showed that SandUp effectively helps build the sandcastle with proper interactive guidance. Based on the results from the user study on children and feedback from their parents, we also derived usability issues that can be further improved and suggested future research directions.

• Journal of Korea Entertainment Industry Association
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• v.13 no.5
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• pp.119-126
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• 2019

Watching movies is common on a big screen like a theater or on a big-screen TV. nowadays, small platform such as mobile devices is increasing rapidly for watch a movie. These changes are deeply related to the advent of Internet-based video streaming services such as OTT. OTT's development has provided in free video viewing system without using the set-top box is free from the limitations of time and space. Leading the market is Netflix[1], which started its business with Internet-based DVD rental service. Netflix, which is growing in tandem with the mobile market, had 193.26[2] million members as of the end of 2018. Other OTT participating companies include content-based Pooq, TVing, platform-based Olleh TV Mobile, Oksusu and LTE video portal. The size of such new growth projects has grown gradually, with 25.4 percent of all smartphone users currently watching video content with small mobile devices. Therefore, de-largeization, it is thought that visual language is needed for viewing small mobile devices that are capable of OTT services. To this end, this paper will identify the problem in viewing popular video content with small mobile devices and Survey and study its impact on viewers using the questionnaire.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.1
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• pp.97-104
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• 2016

In Korea, the number of crash accident victims per 100,000 population is three times higher than the average of OECD. In particular, 60% of it occurs on the community road. Thus, this study intends to analyze the causes of such accidents through a pedestrian and vehicle traffic survey. The purpose is to establish practical safety enhancement measures for community roads. In recent years, lots of changes have occurred in the pedestrian environment. A traffic survey shows that 65% of pedestrians walk on the right and 17% of people use smart-phones while walking. An eye camera experiment shows that the operation load of drivers on the community roads is more than 4 times higher than those in urban roads. According to a speed survey, 62% of vehicles drive at 30km/h or above. The characteristics of accidents on community roads are as follows. First, the ratio of accidents on the edge of the road is 2.3 times as high as those on other roads. Second, when people walk on the right, the ratio of accidents is 2.5 times as high as that of walking on the left. Third, it becomes more dangerous when people cross the road from the right to the left. The majority of accidents is caused by unsafe driving (84.4%). When a vehicle makes a left turn, the likelihood of accidents is 2.3 times as high as those caused by a right turn. The ratio of accidents caused by vehicles going backwards is 14% among all accidents. In community roads, the focus of drivers should be at least 4 times higher than those on urban roads. Thus, walking in the opposite direction of vehicles and careless behaviors are highly likely lead to accidents.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.49-55
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• 2015

According to the statistics of traffic accidents over recent 5 years, traffic accidents during the night times happened more than the day times. There are various causes to occur traffic accidents and the one of the major causes is inappropriate or missing street lights that make driver's sight confused and causes the traffic accidents. In this paper, with smartphones, we designed and implemented a lane luminance measurement application which stores the information of driver's location, driving, and lane luminance into database in real time to figure out the inappropriate street light facilities and the area that does not have any street lights. This application is implemented under Native C/C++ environment using android NDK and it improves the operation speed than code written in Java or other languages. To measure the luminance of road, the input image with RGB color space is converted to image with YCbCr color space and Y value returns the luminance of road. The application detects the road lane and calculates the road lane luminance into the database sever. Also this application receives the road video image using smart phone's camera and improves the computational cost by allocating the ROI(Region of interest) of input images. The ROI of image is converted to Grayscale image and then applied the canny edge detector to extract the outline of lanes. After that, we applied hough line transform method to achieve the candidated lane group. The both sides of lane is selected by lane detection algorithm that utilizes the gradient of candidated lanes. When the both lanes of road are detected, we set up a triangle area with a height 20 pixels down from intersection of lanes and the luminance of road is estimated from this triangle area. Y value is calculated from the extracted each R, G, B value of pixels in the triangle. The average Y value of pixels is ranged between from 0 to 100 value to inform a luminance of road and each pixel values are represented with color between black and green. We store car location using smartphone's GPS sensor into the database server after analyzing the road lane video image with luminance of road about 60 meters ahead by wireless communication every 10 minutes. We expect that those collected road luminance information can warn drivers about safe driving or effectively improve the renovation plans of road luminance management.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.