• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.452-461
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• 2007

Adaptive anti-sway and trajectory tracking control of overhead crane is presented, which utilizes Fuzzy Uncertainty Observer(FUO) and Fuzzy based Variable Structure Control(FVSC). We consider an overhead crane system which can be decoupled into the actuated and unactuated subsystems with its own lumped uncertainty such as parameter uncertainties and external disturbance. First, a new method for anti-sway control using FVSC is proposed to improve the conventional method based on Lyapunov direct method, while a conventional trajectory tracking control law using feedback linearization is directly adopted. Second, FUO is designed to estimate one of the two lumped uncertainties which can compensate both of them, based on the fact that two lumped uncertainties are coupled with each other. Then, an adaptive anti-sway control is proposed by incorporating the proposed FVSC and FUO. Under the condition that the observation error is Uniformly Ultimately Bounded(UUB) within an arbitrarily shrinkable region, the overall closed-loop system is shown to be Globally Uniformly Ultimately Bounded(GUUB). In addition, the Global Asymptotic Stability(GAS) of it is shown under the vanishing disturbance assumption. Finally, the effectiveness of the proposed scheme has been confirmed by numerical simulations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1304-1311
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• 2003

Target tracking in a real world situation is difficult problem because of continuous variations in images, huge amounts of data, and high processing speed demands. The problem becomes even harder in the case of sea background. This paper presents an initial study of neural network based method for target detection and tracking in cluttering environment. The approach uses a combination of differential motion analysis, Kohonen self-organizing network and region growing method. The network is capable of detecting the mass-centers of moving objects within one frame. The history of neurons positions in the sequential frames approximates the traces of the targets. The experiments done with the network in simulated environment showed promising results.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.2 s.7
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• pp.1-11
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• 2005

Automatic tracking of vehicles is important to accurately estimate the vehicle speeds in video-based traffic measurement systems and to analyze traffic flows for road construction. This paper proposes a carefully designed rule-based tracking scheme that considers the possible cases that can be appeared in the video-based vehicle racking. The proposed scheme is fast and outperforms the Mean-Shift scheme in terms of accuracy. The accuracy and the speed of the scheme would be increased by combining it with color-based searching and Kalman filters.

• Journal of Sensor Science and Technology
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• v.23 no.2
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• pp.82-86
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• 2014

This paper reports the development of a platform for tracking and analysis of animal locomotion. The platform is composed of a commercial webcam, a metal stand for the webcam, and a plastic bathtub as a cage. Using it, researchers can track and analyze an animal's movement within the plastic bathtub's dimensions of $100cm{\times}100cm{\times}55cm$ in a cost-effective manner. After recording the locomotion of an animal with $1920{\times}1080$ resolution at a rate of 30 frames per second, finding the position of the animal in each frame and analyzing the ambulation pattern were executed with custom software. To evaluate the performance of the platform, movements of imprinting control region mice and transgenic mice were recorded and analyzed. The analysis successfully compared velocity, moving pattern, and total moving distance for the two mouse groups. In addition, the developed platform can be used not only in simple motion analysis but also in various experimental conditions, such as a water maze, by easy customization of the platform. Such a simple and cost-effective platform yields a powerful tool for animal ambulatory analysis.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.229-235
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• 2011

To make a robust object tracking and identifying system for an intelligent robot and/or home system, heterogeneous sensor fusion between visible ray system and infrared ray system is proposed. The proposed system separates the object by combining the ROI (Region of Interest) estimated from two different images based on a heterogeneous sensor that consolidates the ordinary CCD camera and the IR (Infrared) camera. Human's body and face are detected in both images by using different algorithms, such as histogram, optical-flow, skin-color model and Haar model. Also the pose of human body is estimated from the result of body detection in IR image by using PCA algorithm along with AdaBoost algorithm. Then, the results from each detection algorithm are fused to extract the best detection result. To verify the heterogeneous sensor fusion system, few experiments were done in various environments. From the experimental results, the system seems to have good tracking and identification performance regardless of the environmental changes. The application area of the proposed system is not limited to robot or home system but the surveillance system and military system.

• Korean Journal of Veterinary Research
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• v.60 no.2
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• pp.55-59
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• 2020

This study was purposed to make the referenced range of stomach antral contraction strain in 50 dogs using 2-dimensional speckle tracking. In addition, the strain results were compared among body condition scores to reveal the correlations of obesity among the subjects of the study. Finally, the medetomidine group that was comprised of 10 dogs was compared with the normal group to identify the medetomidine pharmacologic effect in the stomach antral contraction. Clinically healthy 50 dogs were recruited for the study. In an ultrasonographic examination, the stomach antrum region was scanned, and at least one cycle of antral contraction was recorded. The peak strain of antral contraction in healthy dogs was 58.2 ± 20.47% (mean ± SD). The obesity group showed a high strain result and there were significant correlations between the body condition score (BCS) 2, BCS 3 groups and BCS 8 group. The medetomidine group revealed a low strain result and was significantly correlated with normal group. Two-dimensional speckle tracking was useful to the evaluation of stomach motility disorders.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.3965-3983
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• 2017

We propose a novel eye tracking method that can estimate 3D world coordinates using an infrared (IR) stereo camera for indoor and outdoor environments. This method first detects dark evidences such as eyes, eyebrows and mouths by fast multi-level thresholding. Among these evidences, eye pair evidences are detected by evidential reasoning and geometrical rules. For robust accuracy, two classifiers based on multiple layer perceptron (MLP) using gradient local binary patterns (GLBPs) verify whether the detected evidences are real eye pairs or not. Finally, the 3D world coordinates of detected eyes are calculated by region-based stereo matching. Compared with other eye detection methods, the proposed method can detect the eyes of people wearing sunglasses due to the use of the IR spectrum. Especially, when people are in dark environments such as driving at nighttime, driving in an indoor carpark, or passing through a tunnel, human eyes can be robustly detected because we use active IR illuminators. In the experimental results, it is shown that the proposed method can detect eye pairs with high performance in real-time under variable illumination conditions. Therefore, the proposed method can contribute to human-computer interactions (HCIs) and intelligent transportation systems (ITSs) applications such as gaze tracking, windshield head-up display and drowsiness detection.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.29-33
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• 1998

In this paper, we propose a hierarchical segmentation method for tracking a semantic video object using a watershed algorithm based on morphological filtering. In the proposed method, each hierarchy consists of three steps: First, markers are extracted on the simplified current frame. Second, region growing by a modified watershed algorithm is performed for segmentation. Finally, the segmented regions are classified into 3 categories, i.e., inside, outside, and uncertain regions according to region probability values, which are acquired by the probability map calculated from a estimated motion field. Then, for the remaining uncertain regions, the above three steps are repeated at lower hierarchies with less simplified frames until every region is decided to a certain region. The proposed algorithm provides prospective results in video sequences such as Miss America, Clair, and Akiyo.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.6
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• pp.912-917
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• 2009

An experimental flow visualization study of the entrance section of channels formed with wavy plates was made. The experiments were conducted in a water channel and a laser illuminated particle tracking was used as the technique of flow visualization. The flow region that were found in the experiments are steady, unsteady and significantly-mixed flows. Instabilities of the flow first appear near the exit of the channel. As the Reynolds number increases, the flows are characterized by the appearance of flow separation and the growth of recirculation region.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.10B
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• pp.1986-1994
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• 1999

In this paper, a semi-automatic approach is adopted to extract a semantic object from real-world video sequences human-aided segmentation for the first frame and automatic tracking for the remaining frames. The proposed algorithm has a hierarchical structure using watershed algorithm. Each hierarchy consists of 3 basic steps: First, seeds are extracted from the simplified current frame. Second, region growing bv a modified watershed algorithm is performed to get over-segmented regions. Finally, the segmented regions are classified into 3 categories, i.e., inside, outside or uncertain regions according to region probability values, which are acquired by the probability map calculated from an estimated motion-vector field. Then, for the remaining uncertain regions, the above 3 steps are repeated at lower hierarchies with less simplified frames until every region is classified into a certain region. The proposed algorithm provides prospective results in studio-quality sequences such as 'Claire', 'Miss America', 'Akiyo', and 'Mother and daughter'.