• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.308-316
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• 2004

As we know that there are so many restrictions controlling the autonomous robot to turn and move in an indoor space. In this research, Ive adopted the concept ‘Omni-directional wheel’ as a driving equipment, which makes it possible for the robot to move in horizontal and diagonal directions. Most of all, we eliminated the slip error problem, which can occur when the system generates power by means of slip. In order to solve this problem, we developed a ‘slip error correction algorithm’. Following this program, whenever the robot moves in any directions, it defines its course by comparing pre-programmed direction and the current moving way, which can be decided by extracted image of floor line. Additionally, this robot also provides the limited security and service function. It detects the motion of vehicle, transmits pictures to multiple users and can be moved by simple order's. In this paper, we tried to propose a practical model which can be used in an office.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.3
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• pp.329-338
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• 2016

As the need of indoor spatial information has grown, many applications have been developed. Nevertheless, the major representations of indoor spatial information are on the 2D or 3D, recently, the service based on omni-directional image has increased. Current service based on omni-directional image is used just for viewer. To provide various applications which can serve the identifying the attribute of indoor space, query based services and so on, topological data which can define the spatial relationships between spaces is required. For developing diverse applications based on omni-directional image, this study proposes the method to generate IndoorGML data which is the international standard of indoor topological data model. The proposed method is consist of 3 step to generate IndoorGML data; 1) Analysis the core elements to adopt IndoorGML concept to image, 2) Propose the method to identify the element of ‘Space’ which is the core element of IndoorGML concept, 3) Define the connectivity of indoor spaces. The proposed method is implemented at the 6-floor of 21centurybuilding of the University of Seoul to generate IndoorGML data and the demo service is implemented based on the generated data. This study has the significance to propose a method to generate the indoor topological data for the indoor spatial information services based on the IndoorGML.

• Journal of the Korean Society of Visualization
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• v.14 no.2
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• pp.46-51
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• 2016

In this study, a Masked Omni-Directional Integration(MODI) method for pressure calculation is proposed using the Particle Image Velocimetry (PIV) data. To obtain the velocity field, the Affine PIV method was adopted. Synthetic images were generated for a solid body rotation. Calculation on the pressure was based on the Navier-Stokes equation. The results obtained by the MODI were compared with those obtained by theoretical pressure and by the Omni-Directional Integration(ODI) method. It was shown that the minimum error by the proposed MODI method was attained when the mask size was 1.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.3
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• pp.669-675
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• 2005

This paper proposes coordinates transformation and calibration algorithm using 3D parabolic coordinate transformation and delta-bar-delta neural algorithm for the omni-directional image captured by catadioptric camera. Experimental results shows that the proposed algorithm has accuracy and confidence in coordinate transformation which is sensitive to environmental variables.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.210-216
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• 2016

This paper presents a novel collision avoidance technique for mobile robots based on omni-directional vision simultaneous localization and mapping (SLAM). This method estimates the avoidance path and speed of a robot from the location of an obstacle, which can be detected using the Lucas-Kanade Optical Flow in images obtained through fish-eye cameras mounted on the robots. The conventional methods suggest avoidance paths by constructing an arbitrary force field around the obstacle found in the complete map obtained through the SLAM. Robots can also avoid obstacles by using the speed command based on the robot modeling and curved movement path of the robot. The recent research has been improved by optimizing the algorithm for the actual robot. However, research related to a robot using omni-directional vision SLAM to acquire around information at once has been comparatively less studied. The robot with the proposed algorithm avoids obstacles according to the estimated avoidance path based on the map obtained through an omni-directional vision SLAM using a fisheye image, and returns to the original path. In particular, it avoids the obstacles with various speed and direction using acceleration components based on motion information obtained by analyzing around the obstacles. The experimental results confirm the reliability of an avoidance algorithm through comparison between position obtained by the proposed algorithm and the real position collected while avoiding the obstacles.

• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.171-182
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• 2015

We propose a camera system to acquire indoor stereo omni-directional images and its calibration method. These images can be utilized for indoor precise mapping and sophisticated imagebased services. The proposed system is configured with a rotating stereo line camera system, providing stereo omni-directional images appropriate to stable stereoscopy and precise derivation of object point coordinates. Based on the projection model, we derive a mathematical model for the system calibration. After performing the system calibration, we can estimate object points with an accuracy of less than ${\pm}16cm$ in indoor space. The proposed system and calibration method will be applied to indoor precise 3D modeling.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.91-97
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• 2010

This paper describes a development of an network based remote surveillance system using omni-directional mobile robot. the proposed surveillance system can control a mobile robot to move and examines the given place closely while the conventional surveillance system uses a fixed camera. The mobile robot in the proposed system has three omni-directional wheels to move to any given direction freely. We also developed the proposed system as robot services using Microsoft's MSRDS for a user to control the mobile robot and monitor the remote scene captured from the robot. Finally we verified the feasibility and effectiveness of the proposed system by conducting the remote operating the mobile robot and monitoring experiments in a networked environment. We also conducted a color based object detection and motion detection on image sequences acquired from a remote mobile robot in an another PC in a network environment.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.137-140
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• 2008

Recently many areas require wide field of view images. Such as surveillance, virtual reality, navigation and 3D scene reconstruction. Conventional camera systems have a limited filed of view and provide partial information about the scene. however, omni directional vision system can overcome these disadvantages. Acquiring 360 degree panorama images requires expensive omni camera lens. In this study, 360 degree panorama image was tested using a low cost optical reflector which captures 360 degree panoramic views with single shot. This 360 degree panorama image system can be used with detailed positional information from GPS/INS. Through this study result, we show 360 degree panorama image is very effective tool for mobile monitoring system.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.766-772
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• 2015

This paper proposes an object detection method based on motion estimation using background subtraction in the fisheye images obtained through omni-directional camera mounted on the vehicle. Recently, most of the vehicles installed with rear camera as a standard option, as well as various camera systems for safety. However, differently from the conventional object detection using the image obtained from the camera, the embedded system installed in the vehicle is difficult to apply a complicated algorithm because of its inherent low processing performance. In general, the embedded system needs system-dependent algorithm because it has lower processing performance than the computer. In this paper, the location of object is estimated from the information of object's motion obtained by applying a background subtraction method which compares the previous frames with the current ones. The real-time detection performance of the proposed method for object detection is verified experimentally on embedded board by comparing the proposed algorithm with the object detection based on LKOF (Lucas-Kanade optical flow).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.79-84
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• 2005

In this paper, we developed an omni-directional surveillance and motion detection method. The fish-eye lens provides a wide field of view image. Using this image, the equi-distance model for the fish-eye lens is applied to get the perspective and panorama images. Generally, we must consider the trade-off between resolution and field of view of an image from a camera. To enhance the resolution of the result images, some kind of interpolation methods are applied. Also the moving edge method is used to detect moving objects for the object tracking.