• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.345-355
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• 2000

In this paper, the depth controller of an underwater vehicle based on an $H_\infty$ servo control is designed for the depth keeping of the underwater vehicle under wave disturbances. The depth controller is designed in the form of the $H_\infty$ servo controller, which has robust tracking property, and an $H_\infty$ servo problem is considered for the $H_\infty$ servo controller design. In order to solve the $H_\infty$ servo problem for the underwater vehicle, this problem is modified as an $H_\infty$ control problem for the generalized plant that includes a reference input mode, and a suboptimal solution that satisfies a given performance criteria is calculated with the LMI (Linear Matrix Inequality) approach. The $H_\infty$ servo controller is designed to have robust stability about the perturbation of the parameters of the underwater vehicle and the robust tracking property of the underwater vehicle depth under wave force and moment disturbances. The performance, robustness about the uncertainties, and depth tracking property, of the designed depth controller is evaluated by computer simulation, and finally these simulation results show the usefulness and applicability of the proposed $H_\infty$ depth control system.

• The Journal of Korean Institute of Information Technology
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• v.17 no.8
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• pp.75-83
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• 2019

In this paper, we propose a method that can detect and trace the end point of real - time reinforcement steel to various environmental conditions of industrial field by using Median flow and Depth information. We proposed a method to derive two steel end points by using Median filter, Binarization, Morphology, and Blob algorithm on image depth information. The coordinates of the final position were determined by comparing the coordinates of the reinforcement steel endpoints detected in the Depth image and the position tracking coordinates of the reinforcement steel using Median Flow. As a result, when the existing Median Flow method was used, the success rate of the final position determination of reinforcement steel of 75% was increased to 95% when the Depth of reinforcement steel was used.

• ETRI Journal
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• v.35 no.2
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• pp.356-359
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• 2013

We present a method for tracking and interaction based on hybrid sensing for virtual environments. The proposed method is applied to motion tracking of whole areas, including the user's occlusion space, for a high-precision interaction. For real-time motion tracking surrounding a user, we estimate each joint position in the human body using a combination of a depth sensor and a wand-type physical user interface, which is necessary to convert gyroscope and acceleration values into positional data. Additionally, we construct virtual contents and evaluate the validity of results related to hybrid sensing-based whole-body tracking of human motion methods used to compensate for the occluded areas.

• International Journal of Control, Automation, and Systems
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• v.5 no.1
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• pp.51-60
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• 2007

This paper describes a visual tracking control law of an Unmanned Aerial Vehicle(UAV) for monitoring of structures and maintenance of bridges. It presents a control law based on computer vision for quasi-stationary flights above a planar target. The first part of the UAV's mission is the navigation from an initial position to a final position to define a desired trajectory in an unknown 3D environment. The proposed method uses the homography matrix computed from the visual information and derives, using backstepping techniques, an adaptive nonlinear tracking control law allowing the effective tracking and depth estimation. The depth represents the desired distance separating the camera from the target.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.2067-2078
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• 2017

In this paper, a new face tracking algorithm is proposed. The CamShift (Continuously adaptive mean SHIFT) algorithm shows unstable tracking when there exist objects with similar color to that of face in the background. This drawback of the CamShift is resolved by the proposed algorithm using Kinect's pixel-by-pixel depth information and the skin detection method to extract candidate skin regions in HSV color space. Additionally, even when the target face is disappeared, or occluded, the proposed algorithm makes it robust to this occlusion by the feature point matching. Through experimental results, it is shown that the proposed algorithm is superior in tracking performance to that of existing TLD (Tracking-Learning-Detection) algorithm, and offers faster processing speed. Also, it overcomes all the existing shortfalls of CamShift with almost comparable processing time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7A
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• pp.586-599
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• 2012

This paper proposes a fast face detection and tracking method which uses depth images as well as RGB images. It consists of the face detection procedure and the face tracking procedure. The face detection method basically uses an existing method, Adaboost, but it reduces the size of the search area by using the depth image. The proposed face tracking method uses a template matching technique and incorporates an early-termination scheme to reduce the execution time further. The results from implementing and experimenting the proposed methods showed that the proposed face detection method takes only about 39% of the execution time of the existing method. The proposed tracking method takes only 2.48ms per frame with $640{\times}480$ resolution. For the exactness, the proposed detection method showed a little lower in detection ratio but in the error ratio, which is for the cases when a detected one as a face is not really a face, the proposed method showed only about 38% of that of the previous method. The proposed face tracking method turned out to have a trade-off relationship between the execution time and the exactness. In all the cases except a special one, the tracking error ratio is as low as about 1%. Therefore, we expect the proposed face detection and tracking methods can be used individually or in combined for many applications that need fast execution and exact detection or tracking.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.12
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• pp.2980-2988
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• 2000

In this paper, H(sub)$\infty$ depth and course controllers of autonomous underwater vehicles using H(sub)$\infty$ servo control are proposed. An H(sub)$\infty$ servo problem is foumulated to design the controllers satisfying a robust tracking property with modeling errors and disturbances. The solution of the H(sub)$\infty$servo problem is as follows; firest, this problem is modified as an H(sub)$\infty$ control problem for the generalized plant that includes a reference input mode, and than a sub-optimal solution that satisfies a given performance criteria is calculated by LMI(Linear Matrix Inequality) approach, The H(sub)$\infty$depth and course controllers are designed to satisfy the robust stability about the modeling error generated from the perturbation of the hydrodynamic coefficients and the robust tracking property under disturbances(was force, wave moment, tide). The performances(the robustness to the uncertainties, depth and course tracking properties) of the designed controlled are evaluated with computer simulations, and finally these simulation results show the usefulness and applicability of the propose H(sub)$\infty$ depth and course control systems.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.215-215
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• 2000

In this paper, depth and course controllers of autonomous underwater vehicles using H$_{\infty}$ servo control are proposed. An H$_{\infty}$ servo problem is formulated to design the controllers satisfying a robust tracking property with modeling errors and disturbances. The solution of the H$_{\infty}$ servo problem is as follows: first, this problem is modified as an H$_{\infty}$ control problem for the generalized plant that includes a reference input mode, and then a sub-optimal solution that satisfies a given performance criteria is calculated by LMI(Linear Matrix Inequality) approach. The H$_{\infty}$ depth and course controllers ate designed to satisfy with the robust stability about the modeling error generated from the perturbation of the hydrodynamic coefficients and the robust tracking property under disturbances(wave force, wave moment, tide). The performances(the robustness to the uncertainties, depth and course tracking properties) of the designed controllers are evaluated with computer simulations, and finally these simulation results show the usefulness and application of the proposed H$_{\infty}$ depth and course control systems.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.1
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• pp.27-35
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• 2013

This paper proposes a face tracking algorithm for a viewpoint adaptive multi-view synthesis system. The original scene captured by a depth camera contains a texture image and 8 bit gray-scale depth map. From this original image, multi-view images that correspond to the viewer's position can be synthesized using geometrical transformations, such as rotation and translation. The proposed face tracking technique gives a motion parallax cue by different viewpoints and view angles. In the proposed algorithm, the viewer's dominant face, which is established initially from a camera, can be tracked using the statistical characteristics of face colors and deformable templates. As a result, a motion parallax cue can be provided by detecting the viewer's dominant face area and tracking it, even under a heterogeneous background, and synthesized sequences can be displayed successfully.

• Journal of Digital Contents Society
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• v.16 no.6
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• pp.901-908
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• 2015

Networked multiple CCTV systems are required to effectively trace down long-term abnormal behaviors, such as stalking. However, the occluding event, which often takes place during tracking, may result in critical errors of cessation of tracing, or tracking wrong objects. Thus, utilizing installed regular CCTVs, this study aims to trace the relation tracking in a continuous manner by recognizing distinctive features of each object and its perspective projection depth to address the problem with occluded objects. In addition, this study covers occlusion event between the stationary background objects, such as street lights, or walls, and the targeted object.