• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.297-304
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• 1997

In stereo vision, camera modeling is very important because the accuracy of the three dimensional locations depends considerably on it. In the existing stereo camera models, two camera planes are located in the same plane or on the optical axis. These camera models cannot be used in the active vision system where it is necessary to obtain two stereo images simultaneously. In this paper, we propose four kinds of stereo camera models for active stereo vision system where focal lengths of the two cameras are different and each camera is able to rotate independently. A single closed form solution is obtained for all models. The influence of the stereo camera model to the field of view, occlusion, and search area used for matching is shown in this paper. And errors due to inaccurate focal length are analyzed and simulation results are shown. It is expected that the three dimensional locations of objects are determined in real time by applying proposed stereo camera models to the active stereo vision system, such as a mobile robot.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.1
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• pp.35-41
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• 2012

This paper proposes a moving object detection algorithm for active camera system that can be applied to mobile robot and intelligent surveillance system. Most of moving object detection algorithms based on a stationary camera system. These algorithms used fixed surveillance system that does not consider the motion of the background or robot tracking system that track pre-learned object. Unlike the stationary camera system, the active camera system has a problem that is difficult to extract the moving object due to the error occurred by the movement of camera. In order to overcome this problem, the motion of the camera was compensated by using SURF and Pseudo Perspective model, and then the moving object is extracted efficiently using stochastic Label Cluster transport model. This method is possible to detect moving object because that minimizes effect of the background movement. Our approach proves robust and effective in terms of moving object detection in active camera system.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.3
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• pp.314-323
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• 1999

This paper introduces a methodology of active calibration of a camera pose (orientation and position) using the images of cylindrical objects that are going to be manipulated. This active calibration method is different from the passive calibration where a specific pattern needs to be located at a certain position. In the active calibration, a camera attached on the robot captures images of objects that are going to be manipulated. That is, the prespecified position and orientation data of the cylindrical object are transformed into the camera pose through the two consecutive image frames. An ellipse can be extracted from each image frame, which is defined as a circular-feature matrix. Therefore, two circular-feature matrices and motion parameters between the two ellipses are enough for the active calibration process. This active calibration scheme is very effective for the precise control of a mobile/task robot that needs to be calibrated dynamically. To verify the effectiveness of active calibration, fundamental experiments are peformed.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.239-242
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• 2003

In this paper, we propose how to determine the optimal camera position using inverse kinematics of virtual link model and manipulability measure. We model the variable distance and viewing direction between a target object and a camera position as a virtual link. And, by using inverse kinematics of virtual link model, we find out regions that satisfy the direction and distance constraints for the observation of target object. The solution of inverse kinematics of virtual link model simultaneously satisfies camera accessibility as well as a direction and distance constraints. And we use a manipulability measure of active camera system in order to determine an optimal camera position among the multiple solutions of inverse kinematics. By using the inverse kinematics of virtual link model and manipulability measure, the optimal camera position in order to observe a target object can be determined easily and rapidly.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.4
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• pp.427-433
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• 2019

This paper propose a fuzzy inference model for map building and navigation for a mobile robot with an active camera, which is intelligently navigating to the goal location in unknown environments using sensor fusion, based on situational command using an active camera sensor. Active cameras provide a mobile robot with the capability to estimate and track feature images over a hallway field of view. In this paper, instead of using "physical sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data. Command fusion method is used to govern the robot navigation. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a command fusion technique is introduced, where the sensory data of active camera sensor for navigation experiments are fused into the identification process. Navigation performance improves on that achieved using fuzzy inference alone and shows significant advantages over command fusion techniques. Experimental evidences are provided, demonstrating that the proposed method can be reliably used over a wide range of relative positions between the active camera and the feature images.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.4
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• pp.39-43
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• 2004

A typical theme of active vision systems is gaze-fixing of a camera. Here gaze-fixing of a camera means by steering orientation of a camera so that a given point on the object is always at the center of the image. For this we need to combine a function to analyze image data and a function to control orientation of a camera. This paper presents an algorithm for gaze-fixing of a camera where image analysis and orientation control are designed in a frame. At this time, for avoiding difficulties in implementing and aiming for real-time applications we design the algorithm to be a simple closed-form without using my information related to calibration of the camera or structure estimation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.2
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• pp.344-352
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• 2003

An effective algorithm for implementation of which detects moving object from image sequences. predicts the direction of it. and drives the camera in real time is proposed. In static camera, for robust motion detection from a dynamic background scene, the proposed algorithm performs statistical modeling of moving objects and background, and trains the statistical modeling of moving objects and background, and trains the statistical feature of background with the initial parts of sequence which have no moving objects. Active camera moving objects are segmented by following procedure, an improved order adaptive lattice structured linear predictor is used. The proposed algorithm shows robust object tracking results in the environment of static or active camera. It can be used for the unmanned surveillance system, traffic monitoring system, and autonomous vehicle.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.407-412
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• 2009

In the present work, vibration control performance of active camera mount system for unmanned aero vehicle (UAV) is evaluated. An active mount featuring inertia type of piezostack actuator is designed and manufactured. Then, vibration control performances are experimentally evaluated. A camera mount system with four active mounts is constructed and mechanical model is established. The governing equation for the camera mount system is obtained and control model is constructed in state space model. Sliding mode controller which has inherent robustness to external disturbance is designed and implemented to the system. Vibration control performances are evaluated at each mount and center of gravity point. Effective vibration performances are obtained and presented in time and frequency domains.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.257-259
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• 1996

This paper presents the active eye system for tracking a moving object in 3D space. A prototype system able to track a moving object is designed and implemented. The mechanical system ables the control of platform that consists of binocular camera and also the control of the vergence angle of each camera by step motor. Each camera has two degrees of freedom. The image features of the object are extracted from complicated environment by using zero disparity filtering(ZDF). From the cnetroid of the image features the gaze point on object is calculated and the vergence angle of each camera is controlled by step motor. The Proposed method is implemented on the prototype with robust and fast calculation time.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.12
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• pp.1315-1321
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• 2009

In the present work, vibration control performance of active camera mount system for unmanned aero vehicle(UAV) is evaluated. An active mount featuring inertia type of piezostack actuator is designed and manufactured. Then, vibration control performances are experimentally evaluated. A camera mount system with four active mounts is constructed and mechanical model is established. The governing equation for the camera mount system is obtained and control model is constructed in state space model. Sliding mode controller which has inherent robustness to external disturbance is designed and implemented to the system. Vibration control performances are evaluated at each mount and center of gravity point. Effective vibration performances are obtained and presented in time and frequency domains.