• The Journal of Korea Robotics Society
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• v.2 no.2
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• pp.129-136
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• 2007

This paper introduces a position-based robust visual servoing method which is developed for operation of a human-like robot with two arms. The proposed visual servoing method utilizes SIFT algorithm for object detection and CAMSHIFT algorithm for object tracking. While the conventional CAMSHIFT has been used mainly for object tracking in a 2D image plane, we extend its usage for object tracking in 3D space, by combining the results of CAMSHIFT for two image plane of a stereo camera. This approach shows a robust and dependable result. Once the robot's task is defined based on the extracted 3D information, the robot is commanded to carry out the task. We conduct several position-based visual servoing tasks and compare performances under different conditions. The results show that the proposed visual tracking algorithm is simple but very effective for position-based visual servoing.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.1
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• pp.39-45
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• 2019

We propose an active color model based method for tracking motions of multiple human using a networked multiple-camera system in IoT space as a human-robot coexistent system. An IoT space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of IoT space as well. One of the main goals of IoT space is to assist humans and to do different services for them. In order to be capable of doing that, IoT space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly. In the environment where many camera modules are distributed on network, it is important to identify object in order to track it, because different cameras may be needed as object moves throughout the space and IoT space should determine the appropriate one. This paper describes appearance based unknown object tracking with the distributed vision system in IoT space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

• Journal of Astronomy and Space Sciences
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• v.30 no.4
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• pp.279-290
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• 2013

Due to the continuous space development by mankind, the number of space objects including space debris in orbits around the Earth has increased, and accordingly, difficulties of space development and activities are expected in the near future. In this study, among the stages for space debris removal, the implementation of a vision-based approach technique for approaching space debris from a far-range rendezvous state to a proximity state, and the ground test performance results were described. For the vision-based object tracking, the CAM-shift algorithm with high speed and strong performance, and the Kalman filter were combined and utilized. For measuring the distance to a tracking object, a stereo camera was used. For the construction of a low-cost space environment simulation test bed, a sun simulator was used, and in the case of the platform for approaching, a two-dimensional mobile robot was used. The tracking status was examined while changing the position of the sun simulator, and the results indicated that the CAM-shift showed a tracking rate of about 87% and the relative distance could be measured down to 0.9 m. In addition, considerations for future space environment simulation tests were proposed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.2
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• pp.217-226
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• 2006

Extraction and tracking objects are fundamental and important steps of the digital image processing and computer vision. Many algorithms about extracting and tracking objects have been developed. In this research, a method is suggested for tracking a moving object using a pair of CCD cameras and calculating the coordinate of the moving object. A 1/100 miniature of soccer field was made to apply the developed algorithms. After candidates were selected from the acquired images using the RGB value of a moving object (soccer ball), the object was extracted using its size (MBR size) among the candidates. And then, image coordinates of a moving object are obtained. The real-time position of a moving object is tracked in the boundary of the expected motion, which is determined by centering the moving object. The 3D position of a moving object can be obtained by conducting the relative orientation, absolute orientation, and space intersection of a pair of the CCD camera image.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.9 s.174
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• pp.77-84
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• 2005

In most vision applications, we are frequently confronted with determining the position of object continuously. Generally, intertwined processes ire needed for target tracking, composed with tracking and control process. Each of these processes can be studied independently. In case of actual implementation we must consider the interaction between them to achieve robust performance. In this paper, the robust real time visual tracking in complex background is considered. A common approach to increase robustness of a tracking system is to use known geometric models (CAD model etc.) or to attach the marker. In case an object has arbitrary shape or it is difficult to attach the marker to object, we present a method to track the target easily as we set up the color and shape for a part of object previously. Robust detection can be achieved by integrating voting-based visual cues. Kalman filter is used to estimate the motion of moving object in 3D space, and this algorithm is tested in a pan/tilt robot system. Experimental results show that fusion of cues and motion estimation in a tracking system has a robust performance.

• Journal of information and communication convergence engineering
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• v.10 no.3
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• pp.307-314
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• 2012

This paper reports on the design of an object tracker that utilizes a family of unscented Kalman filters, one for each tracked object. This is a more efficient design than having one unscented Kalman filter for the family of all moving objects. The performance of the designed and implemented filter is demonstrated by using simulated movements, and also for object movements in 2D and 3D space.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.149-156
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• 2005

In the actuality that the various services are provided in connection with the network of internet by activating the communication using Propagation, the importance of the feature point and chase of an object is greatly raised to increase the quality of the detection and tracking of the communication service. This paper is to detect the shadow space by using Snakes Algorithms and Present a system's base which tracts the route from start to target points in the detected shadow space as a study for the detection and tracking the shadow space which does not reach the propagation.

• Journal of the Korean Society of Systems Engineering
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• v.20 no.1
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• pp.76-84
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• 2024

This study investigates the design of an optical observation system for continuously tracking unknown space object targets within the telescope's field of view at a short cycle rate of several to tens of frames per second. Through modeling and integrated simulation by design variables, we aim to identify combinations that satisfy the performance effectiveness scale. The study demonstrates the effectiveness of a model-based simulation analysis approach in rapidly identifying design parameters that meet specific performance requirements. By leveraging numerical models tailored to the desired performance analysis level, the approach provides a robust foundation for decision-making, eliminating reliance on empirical methods or vague estimations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.868-871
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• 2009

We propose an global color model based method for tracking motions of multiple human using a networked multiple-camera system in intelligent space as a human-robot coexistent system. An intelligent space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of intelligent space as well. One of the main goals of intelligent space is to assist humans and to do different services for them. In order to be capable of doing that, intelligent space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.950-953
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• 2007

The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd.