As the number of tourists visiting Seoul are continuously increasing, the demand of an integrative tour pass is also increasing. However, only a few tour passes are available for the tourists in Seoul. In this paper, we propose a new tour pass called “Seoul Landmark Pass” targeting foreign individual travelers and investigate the marketability of the proposed tour pass. For the configuration of the Seoul Landmark Pass we listed 17 candidate attractions charging entrance fee in Seoul, referring to e-guidebook on Visit Seoul web site. Among them we selected 6 attractions using the checklist with the attributes that foreign tourists would prefer. We also performed SWOT analyzes on existing tour passes to determine the benefits to be included in the proposed tour pass. To investigate the marketability of the proposed tour pass we have surveyed the foreign individual tourists in Seoul. Using the survey data, we have analyzed the intent of purchase by age, visiting period, visiting purpose, frequency of visit, and nationality to identify target customers. The results show that the intent of purchase is high among the Chinese tourists at the age of twenties who visited Seoul for the first time or second times. Also, the individual tourists prefer to bundle T-money card with the proposed tour pass. Finally, we have provided a brief review of the Price Sensitivity Measurement (PSM) method and applied PSM to determine the acceptable price range and the optimal price of the proposed tour pass. The optimal price of the proposed tour pass is determined at 53,000 won including T-money card.

This study introduces the web-camera image processing-based natural landmark extraction method for automatic welding using 3-axis stage. The welding is a highly significant process in the industries of shipbuilding, automobile, construction, machinery, and so on. However, it has been avoided due to poor working conditions such as fume, spatter, noise, and so on. For the automatic welding system, the web-camera is used to extract the natural landmarks which can give the relative coordinate to set up the initial position of the stage for the welding process. The Canny edge and Hough transformation have been used to extract the significant points for the natural landmark extraction in this paper.

This study is the result of the survey on perception and anxiety of high - rise buildings in the general public. As a result of the survey, there was insufficient change in awareness before the construction of high - rise buildings such as landmarks was insufficient (before 2015). However, half of the citizens who felt uneasy that high-rise buildings were likely to collapse due to external influences were close. The anxiety was mainly due to the information of the press or the Internet. It is thought that the cause of anxiety comes from touching negative opinions about the high-rise buildings.

The localization of the robot is one of the most important factors of navigating mobile robots. The use of featured information of landmarks is one approach to estimate the location of the robot. This approach can be classified into two categories: the natural-landmark-based and artificial-landmark-based approach. Natural landmarks are suitable for any environment, but they may not be sufficient for localization in the less featured or dynamic environment. On the other hand, artificial landmarks may generate shaded areas due to space constraints. In order to improve these disadvantages, this paper presents a novel development of the localization system by using artificial and natural-landmarks-based approach on a topological map. The proposed localization system can recognize far or near landmarks without any distortion by using landmark tracking system based on top-view image transform. The camera is rotated by distance of landmark. The experiment shows a result of performing position recognition without shading section by applying the proposed system with a small number of artificial landmarks in the mobile robot.

The landmark-based morphometric and meristic analysis of the kelp grouper (Epinephelus bruneus), red spotted grouper (E. akaara) and seven-banded grouper (E. septemfasciatus) were performed to compare the differentiation of overall body shape and structure. The measurements of the morphometric dimensions were observed in 25 parts (truss dimension: 16 parts; head part dimension: 9 parts) of 38 morphometric dimensions and also meristic differences observed in 3 parts (dorsal fin, anal fin and caudal fin) of 6 meristic counts (P < 0.05). Observed morphometric characteristics primarily involved in truss and head part dimension, kelp grouper have larger values in caudal part of truss dimension, kelp grouper, red spotted grouper and seven-banded grouper have similar values in pectoral part of truss dimension, in addition to, results of head part dimension showed that red spotted grouper have smaller values in overall dimensions (P < 0.05). As meristic characteristics, kelp grouper have more number of anal fin rays than other fish, red spotted grouper have more number of dorsal soft rays than other fish, and seven spotted grouper have more number of anal soft rays, and caudal fin rays than other fish (P < 0.05). Photographed under the x-ray, kelp grouper have the most curved vertebral column and largest swim bladder than other fishes (P < 0.05). Our results of this study confirmed that 3 subfamily fishes adequately can distinguish with external body shape, and we hope that the results of our study could be used to identify in Serranidae family as taxonomical parameters.

This paper proposes a pose-graph based SLAM method using an upward-looking camera and artificial landmarks for AGVs in factory environments. The proposed method provides a way to acquire the camera extrinsic matrix and improves the accuracy of feature observation using a low-costcamera. SLAM is conducted by optimizing AGV’s explored path using the artificial landmarks installed on the ceiling at various locations. As the AGV explores, the pose nodes are added based on the certain distance from odometry and the landmark nodes are registered when AGV recognizes the fiducial marks. As a result of the proposed scheme, a graph network is created and optimized through a G2O optimization tool so that the accumulated error due to the slip is minimized. The experiment shows that the proposed method is robust for SLAM in real factory environments.

This paper propose a localization system of indoor mobile robots. The localization system includes camera and artificial landmarks for global positioning, and encoders and gyro sensors for local positioning. The Kalman filter is applied to take into account the stochastic errors of all sensors. Also we develop a dead reckoning system to estimate the global position when the robot moves the blind spots where it cannot see artificial landmarks, The learning engine using modular networks is designed to improve the performance of the dead reckoning system. Experimental results are then presented to verify the usefulness of the proposed localization system.

To achieve autonomous mobile robot navigation, accurate localization technique is the fundamental issue that should be addressed. In augmented reality, the position of a user is required for location-based services. This paper presents indoor localization using infrared reflective artificial landmarks. In order to minimize the disturbance to the user and to provide the ease of installation, the passive landmarks are used. The landmarks are made of coated film which reflects the infrared light efficiently. Infrared light is not visible, but the camera can capture the reflected infrared light. Once the artificial landmark is identified, the camera’s relative position/orientation is estimated with respect to the landmark. In order to reduce the number of the required artificial landmarks for a given environment, the pan/tilt mechanism is developed together with the distortion correction algorithm.