• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1459-1466
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• 2018

Robots which detect human and recognize action are important factors for human interaction, and many researches have been conducted. Recently, deep learning technology has developed and learning based robot's technology is a major research area. These studies require a database to learn and evaluate for intelligent human perception. In this paper, we propose a multi-modal sensor-based image database condition considering the security task by analyzing the image database to detect the person in the outdoor environment and to recognize the behavior during the running of the robot.

• Proceedings of the KIEE Conference
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• 2004.07c
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• pp.1832-1834
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• 2004

The degree of contamination on outdoor insulator is one of the most importance factors to determine the pollution level of outdoor insulations, and the sea salt is known as the most dangerous pollutant. As shown through the preceding study, the generation of salt pollutant and the pollution degree of outdoor insulator have a close relation with meteorological conditions, such as wind velocity, rainfall, and so on. So, in this paper, we have made database using the past meteorological data and ESDD(equivalent salt deposit density) and then we predicted the pollution degree in the future after analyzing currently meteorological data of database.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1139-1145
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• 2008

A robust position sensing system is proposed in this paper for a ubiquitous mobile robot which moves indoors as well as outdoors. The Differential GPS (DGPS) which has a position estimation error of less than 5 m is a general solution when the mobile robot is moving outdoor, while an active beacon system (ABS) with embedded ultrasonic sensors is reliable as an indoor positioning system. The switching from the outdoor to indoor or vice versa causes unstable measurements on account of the reference coordinates and algorithm changes. To minimize the switching time in the position estimation and to stabilize the measurement, a robust position sensing system is proposed. In the system, to minimize the switching delay, the door positions are stored and updated in a database. Using the database, the approaching status of the mobile robot from indoor to outdoor or vice versa has been checked and the switching conditions are prepared before the mobile robot actually moves out or moves into the door. The reliability and accuracy of the robust positioning system based on DGPS and ABS are verified and demonstrated through the real experiments using a mobile robot prepared for this research.

• Journal of Korea Multimedia Society
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• v.19 no.9
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• pp.1647-1658
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• 2016

RGB+D database has been widely used in object recognition, object tracking, robot control, to name a few. While rapid advance of active depth sensing technologies allows for the widespread of indoor RGB+D databases, there are only few outdoor RGB+D databases largely due to an inherent limitation of active depth cameras. In this paper, we propose a novel method used to build outdoor RGB+D databases. Instead of using active depth cameras such as Kinect or LIDAR, we acquire a pair of stereo image using high-resolution stereo camera and then obtain a depth map by applying stereo matching algorithm. To deal with estimation errors that inevitably exist in the depth map obtained from stereo matching methods, we develop an approach that estimates confidence of depth maps based on unsupervised learning. Unlike existing confidence estimation approaches, we explicitly consider a spatial correlation that may exist in the confidence map. Specifically, we focus on refining confidence feature with the assumption that the confidence feature and resultant confidence map are smoothly-varying in spatial domain and are highly correlated to each other. Experimental result shows that the proposed method outperforms existing confidence measure based approaches in various benchmark dataset.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.3
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• pp.185-196
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• 2018

In order to overcome the problem that outdoor and indoor spatial information service are separately utilized, an integration service system of spatial information that is linked from outdoor to indoor has been implemented. As a result of the study, "0001.xml" corresponding to the file index key value, which is the service connection information in the building information of the destination, was extracted from the prototype verification of the system, the search word of 'Kim AB' was transmitted to the indoor map server and converted from the outdoor map service to the indoor map service through confirmation of the navigation service connected information, using service linkage information and search words of the indoor map service was confirmed that the route was displayed from the entrance of the building to the destination in the building through the linkage search DB (Database) table and the search query. Therefore, through this study was examined the possibility of linking indoor and outdoor DB through vector spatial information integration service system. The indoor map and the map engine were implemented based on the same vector map format as the outdoor map engine, it was confirmed that the connectivity of the map engine can be applied.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.221-226
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• 2007

A robust position-sensing system is proposed in this paper for ubiquitous mobile robots which move indoor as well as outdoor. The Differential GPS (DGPS) which has position estimation error of less than 5 m is a general solution when the mobile robots are moving outdoor, while an active beacon system (ABS) with embedded ultrasonic sensors is selected as an indoor positioning system. The switching from the outdoor to indoor or vice versa causes unstable measurements on account of the reference and algorithm changes. To minimize the switching time in the position estimation and to stabilize the measurement, a robust position-sensing system is proposed. In the system, to minimize the switching delay, the door positions are stored and updated in a database. The reliability and accuracy of the robust positioning system based on DGPS and ABS are verified through the real experiments using a mobile robot prepared for this research and demonstrated.

• Agribusiness and Information Management
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• v.7 no.1
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• pp.1-9
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• 2015

The purpose of this study is to develop a growth prediction model that can predict growth and development information influencing the production of citrus fruits: the growth model algorithm that can predict floral leaf ratio, number of fruit sets, fruit width, and overweight depending on the main period of growth and development with consideration of the applied weather factors. Every year, large scale of manpower was mobilized to investigate the production of outdoor-grown citrus fruits, but it was limited to recycling the data without an observation supporting system to systemize the database. This study intends to create a systematical database based on the basic data obtained through the observation supporting system in application of an algorithm according to the accumulated long term data and prepare a base for its continuous improvement and development. The importance of the observed data is increasingly recognized every year, and the citrus fruit observation supporting system is important for utilizing an effective policy and decision making according to various applications and analysis results through an interconnection and an integration of the investigated statistical data. The citrus fruit is a representative crop having a great ripple effect in Jeju agriculture. An early prediction of the growth and development information influencing the production of citrus fruits may be helpful for decision making in supply and demand control of agricultural products.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.277-285
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• 2010

This paper describes an approach to analyze geometrical information of building images for understanding outdoor environment of autonomous navigation robot. Line segments and color information are used to classily a building with the other objects such as sky, trees, and roads. The line segments and their two neighboring regions are extracted from detected edges in image. The model of line segment (MLS) consists of color information of neighbor regions. This model rules out the line segments of non-building face. A building face converges into dominant vanishing points (DVPs) which include one vertical point and one of five horizontal points in maximum. The intersection of vertical and horizontal lines creates a facet of building. The geometrical characteristics such as the center coordinates, area, aspect ratio and aligned coexistence are used for extracting the windows in the building facet. In experiments, 150 building faces and 1607 windows were detected from the database of outdoor environment. We found that this result shows 94.46% detection rate. These experimental images were all taken in Ulsan metropolitan city in Korea under difference of viewpoints, daytime, camera system and weather condition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.8
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• pp.1655-1666
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• 2015

In this paper, user-position estimation method is proposed by using a single camera for both indoor and outdoor environments. Conventionally, the GPS of RF-based estimation methods have been widely studied in the literature for outdoor and indoor environments, respectively. Each method is useful only for indoor or outdoor environment. In this context, this study adopts a vision-based approach which can be commonly applicable to both environments. Since the distance or position cannot be extracted from a single still image, the reference images pro-stored in image database are used to identify the current position from the single still image captured by a single camera. The reference image is tagged with its captured position. To find the reference image which is the most similar to the current image, the SURF algorithm is used for feature extraction. The outliers in extracted features are discarded by using RANSAC algorithm. The performance of the proposed method is evaluated for two buildings and their outsides for both indoor and outdoor environments, respectively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.48-55
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• 2009

Prior research works in indoor-outdoor classification have been conducted based on a simple combination of low-level features. However, since there are many challenging problems due to the extreme variability of the scene contents, most methods proposed recently tend to combine the low-level features with high-level information such as the presence of trees and sky. To extract these regions from videos, we need to conduct additional tasks, which may yield the increasing number of feature dimensions or computational burden. Therefore, an efficient indoor-outdoor scene classification method is proposed in this paper. First, the video is divided into the five same-sized blocks. Then we define and use the edge and color orientation histogram (ECOH) descriptors to represent each sub-block efficiently. Finally, all ECOH values are simply concatenated to generated the feature vector. To justify the efficiency and robustness of the proposed method, a diverse database of over 1200 videos is evaluated. Moreover, we improve the classification performance by using different weight values determined through the learning process.