• Journal of the Institute of Electronics Engineers of Korea CI
• /
• 제44권3호
• /
• pp.57-67
• /
• 2007

Researchers in mobile AR systems have so far put the value on the technical challenges involved in the limitations imposed from mobility. Beyond such immediate technical questions, however, are questions regarding the possible contents that are to be used for the user’s interaction in ubiquitous computing environment. Various aspects of context of user and environment can be utilized easily as well as effectively. Moreover, the environment will be equipped with lots of pervasive but invisible computing resources. However, it is difficult for users to have access to those computing resources. At the same time, as the smart appliances get to have more features, their user interfaces tend to become harder to use. Thus, in this paper, we propose Context-Aware Mobile Augmented Reality (CAMAR) system. In our system, users only need to take a picture of smart appliances with a built-in camera in a mobile device when they intend to control the appliances. It lets users interact with the smart appliances through personalized control interfaces on their mobile devices. Also, it supports enabling contents to be not only personalized but also shared selectively and interactively among user communities.

• Journal of Internet Computing and Services
• /
• 제15권6호
• /
• pp.27-34
• /
• 2014

Todays, the rapid technical progress of smart device has been used for various social (wall-fare) services in our lives. Especially, most of these services are based on the Local-based Services (LBS) and this technology is getting popular more and more compared with before. Basically, LBS is able to support various types of geographical services such as vehicles' navigation services, Augmented reality services as using extensional local information such as GPS. However, LBS has serious mathematical vulnerability on the services frequently because of its miscalculated GPS data under interior and ambiguous geographical environment such like shadowed area. So, to overcome this limitation, iBeacon, which would be able to mitigate LBS miscalculation process, has been proposed recently among network experts. Compared with other wireless technologies, iBeacon is able to determine the accurate geographical data of certain local positions easily because it is not only designed based on low-powered data transmitting technology, but also, it can be much easy to be deployed. As users' dependency of smart devices are getting higher and higher and the use of smart device is also getting complex more and more, the users prefer to use various types of smart devices at one time. Therefore, in this paper, we propose the loss prevention system that is able to interwork smart devices networks as using iBeacon technology for users' better conveniences.

• Journal of Internet Computing and Services
• /
• 제12권1호
• /
• pp.99-110
• /
• 2011

Mobile environments rapidly changing and digital convergence widely employed, mobile devices including smart phones have been playing a critical role that changes users' lifestyle in the areas of entertainments, businesses and information services. The various services using mobile devices are developing to meet the personal needs of users in the mobile environments. Especially, an LBS (Location-Based Service) is combined with other services and contents such as augmented reality, mobile SNS (Social Network Service), games, and searching, which can provide convenient and useful services to mobile users. In this paper, we design and implement the prototype of mobile personal assistant (PA) agents. Our personal assistant agent helps users do some tasks by hiding the complexity of difficult tasks, performing tasks on behalf of the users, and reflecting the preferences of users. To identify user's preferences and provide personalized services, clustering and classification algorithms of data mining are applied. The clusters of the log data using clustering algorithms are made by measuring the dissimilarity between two objects based on usage patterns. The classification algorithms produce user profiles within each cluster, which make it possible for PA agents to provide users with personalized services and contents. In the experiment, we measured the classification accuracy of user model clustered using clustering algorithms. It turned out that the classification accuracy using our method was increased by 17.42%, compared with that using other clustering algorithms.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• 제30권2호
• /
• pp.211-221
• /
• 2012

To utilize omni-directional images acquired by a rotating line camera for indoor spatial information services, we should register precisely the images with respect to an indoor coordinate system. In this study, we thus develop a georeferencing method to estimate the exterior orientation parameters of an omni-directional image - the position and attitude of the camera at the acquisition time. First, we derive the collinearity equations for the omni-directional image by geometrically modeling the rotating line camera. We then estimate the exterior orientation parameters using the collinearity equations with indoor control points. The experimental results from the application to real data indicate that the exterior orientation parameters is estimated with the precision of 1.4 mm and $0.05^{\circ}$ for the position and attitude, respectively. The residuals are within 3 and 10 pixels in horizontal and vertical directions, respectively. Particularly, the residuals in the vertical direction retain systematic errors mainly due to the lens distortion, which should be eliminated through a camera calibration process. Using omni-directional images georeferenced precisely with the proposed method, we can generate high resolution indoor 3D models and sophisticated augmented reality services based on the models.

• Spatial Information Research
• /
• 제21권4호
• /
• pp.83-89
• /
• 2013

Recently various contents have been produced using the techniques that require high-performance computing process. A lot of services have been being producted as AR(Augmented Reality) service being combined with mobile information service that a moving user search various information based on one's location with. Mobile information service has a characteristic that it needs to get new information according to the location an user moves to. The characteristic requires a lot of communications when user search information moving to a different location. In order to make up for this drawback, we propose a prefetching technique based on speed and viewing angle in this paper. Existing prefetching techniques retrieve the following location of users considering moving speed and direction of the users. The data showed on the screen in AR is limited by the viewing angle of the mobile device. Due to the problems we discussed above, existing prefetching techniques have a demerit that they retrieve a lot more data than needed actually. We propose more efficient way of retrieving data with AR using the viewing angle of the mobile device. The method we propose reduces retrieval of unnecessary location using the users' speed, direction and viewing angle. This method is more efficient than the existing ways of retrieval because we don't need as many data.

• The Journal of the Convergence on Culture Technology
• /
• 제4권1호
• /
• pp.337-351
• /
• 2018

This paper discusses 5G IOT, Augmented Reality, Cloud Computing, Big Data, Future Autonomous Driving Vehicle technology, and presents 5G utilization of Pyeongchang Winter Olympic Games and Jeju Smart City model. The reason is that 5G is the main artery of the 4th industry.5G is the fourth industrial aorta because 5G is the core infrastructure of the fourth industrial revolution. In order for the AI, autonomous vehicle, VR / AR, and Internet (IoT) era to take off, data must be transmitted several times faster and more securely than before. For example, if you send a stop signal to LTE, which is a communication technology, to a remote autonomous vehicle, it takes a hundredth of a second. It seems to be fairly fast, but if you run at 100km / h, you can not guarantee safety because the car moves 30cm until it stops. 5G is more than 20 gigabits per second (Gbps), about 40 times faster than current LTE. Theoretically, the vehicle can be set up within 1 cm. 5G not only connects 1 million Internet (IoT) devices within a radius of 1 kilometer, but also has a speed delay of less than 0.001 sec. Steve Mollenkov, chief executive officer of Qualcomm, the world's largest maker of smartphones, said, "5G is a key element and innovative technology that will connect the future." With 5G commercialization, there will be an economic effect of 12 trillion dollars in 2035 and 22 million new jobs We can expect to see the effect of creation.

• KIPS Transactions on Software and Data Engineering
• /
• 제5권6호
• /
• pp.307-312
• /
• 2016

Markerless tracking for augmented reality using Homography can augment virtual objects correctly and naturally on live view of real-world environment by using correct pose and direction of camera. The RANSAC algorithm is widely used for estimating Homography. CS-RANSAC algorithm is one of the novel algorithm which cooperates a constraint satisfaction problem(CSP) into RANSAC algorithm for increasing accuracy and decreasing processing time. However, CS-RANSAC algorithm can be degraded performance of calculating Homography that is caused by selecting feature points which estimate low accuracy Homography in the sampling step. In this paper, we propose feature point filtering method based on CS-RANSAC for efficient planar Homography estimating the proposed algorithm evaluate which feature points estimate high accuracy Homography for removing unnecessary feature point from the next sampling step using Symmetric Transfer Error to increase accuracy and decrease processing time. To evaluate our proposed method we have compared our algorithm with the bagic CS-RANSAC algorithm, and basic RANSAC algorithm in terms of processing time, error rate(Symmetric Transfer Error), and inlier rate. The experiment shows that the proposed method produces 5% decrease in processing time, 14% decrease in Symmetric Transfer Error, and higher accurate homography by comparing the basic CS-RANSAC algorithm.

• 재활복지
• /
• 제22권3호
• /
• pp.225-257
• /
• 2018

The purpose of this study is to find the application point of hearing augmentation technology development through examining the risk context experience of people with hearing impairment and the use of assistive device used as an alternative technology. Data of 355 people with hearing impairment with official disability grading was analyzed. The results of this study are first, research participants had no experience of recognizing any sound or vibration in situations highest in the order of means of transportation, material, and nature. Especially the ratio of being unable to recognize the sound and vibration of means of transportation was high, which implies the high possibility of people with hearing impairment experiencing risk. Secondly, the risk context that people with hearing impairment will most likely to experience are highest in the order of traffic accident, pedestrian accident, and daily life at home. Thirdly, the recognition of 2G phone/smart phone, vibrating digital alarm clock, light bar, vibrating wrist watch as assistive device for risk context awareness and notification was high and the satisfaction level of 2G phone/smart phone was the highest. Fourthly, the research participants had high recognition of assistive device for communication in the order of hearing aid, smart phone, videophone, cochlear implant and 2G phone and it was found that the satisfaction level and communication improvement level was the highest using the smart phone. Lastly, for the development of hearing augmentation technology the research participants recognized the importance of portable/wear convenience, price, and motion accuracy and for notification delivery means they preferred the method of using sight(text and light). Based on the results of this study policy and practical plans for hearing augmentation technology development for people with hearing impairment in risk context are proposed.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• 제21권3호
• /
• pp.59-66
• /
• 2021

Humans mainly recognize surrounding objects using visual and auditory information among the five senses (sight, hearing, smell, touch, taste). Major research related to the latest object recognition mainly focuses on analysis using image sensor information. In this paper, after emitting various chirp audio signals into the observation space, collecting echoes through a 2-channel receiving sensor, converting them into spectral images, an object recognition experiment in 3D space was conducted using an image learning algorithm based on deep learning. Through this experiment, the experiment was conducted in a situation where there is noise and echo generated in a general indoor environment, not in the ideal condition of an anechoic room, and the object recognition through echo was able to estimate the position of the object with 83% accuracy. In addition, it was possible to obtain visual information through sound through learning of 3D sound by mapping the inference result to the observation space and the 3D sound spatial signal and outputting it as sound. This means that the use of various echo information along with image information is required for object recognition research, and it is thought that this technology can be used for augmented reality through 3D sound.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• 제22권2호
• /
• pp.63-70
• /
• 2022

Although 2D Object detection has been largely improved in the past years with the advance of deep learning methods and the use of large labeled image datasets, 3D object detection from 2D imagery is a challenging problem in a variety of applications such as robotics, due to the lack of data and diversity of appearances and shapes of objects within a category. Google has just announced the launch of Objectron that has a novel data pipeline using mobile augmented reality session data. However, it also is corresponding to 2D-driven 3D object detection technique. This study explores more mature 2D object detection method, and applies its 2D projection to Objectron 3D lifting system. Most object detection methods use bounding boxes to encode and represent the object shape and location. In this work, we explore a stochastic representation of object regions using Gaussian distributions. We also present a similarity measure for the Gaussian distributions based on the Hellinger Distance, which can be viewed as a stochastic Intersection-over-Union. Our experimental results show that the proposed Gaussian representations are closer to annotated segmentation masks in available datasets. Thus, less accuracy problem that is one of several limitations of Objectron can be relaxed.