• Sleep Medicine and Psychophysiology
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• v.9 no.2
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• pp.122-126
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• 2002

Objectives: The purpose of this study is to investigate the effects of the 37-hour sleep deprivation on visual discrimination using the Cybernetic Flicker Fusion Analyzer (FLIMK) and to see the correlation between this finding and various subjective scale scores. Methods: Twenty six subjects (20 men 6 women, $24.50{\pm}1.45$ years of age) participated in this study. Subjects remained awake for 37 hours under continuous surveillance. In the morning and evening of two study days, the FLIMK and the self-reporting scale of sleepiness, fatigue, anxiety and mood states were instituted. Results: In FLIMK, the flicker fusion threshold was significantly decreased after sleep deprivation (F=7.66, p=0.01). The number of trials (responses) before reaching fusion frequency threshold was significantly increased after sleep deprivation (F=13.16, p=0.001). The reduction of fusion frequency was correlated with the increase of sleepiness and fatigue (p<0.05), and the number of the trials was correlated with the scores of negative mood, anxiety, and fatigue (p<0.05). Conclusions: These results suggest that 37 hour total sleep deprivation cause the decrement in visual discrimination. The decrease of the fusion frequency after sleep deprivation was correlated with sleepiness and fatigue. Further study is needed to enlighten the biological mechanism of the decrement in visual function after sleep deprivation.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.313-326
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• 2018

This paper introduces core techniques on ship detection and tracking based on a compact HF radar platform which is necessary to establish a wide-area surveillance network. Currently, most HF radar sites are primarily optimized for observing sea surface radial velocities and bearings. Therefore, many ship detection systems are vulnerable to error sources such as environmental noise and clutter when they are applied to these practical surface current observation purpose systems. In addition, due to Korea's geographical features, only compact HF radars which generates non-uniform antenna response and has no information on target information are applicable. The ship detection and tracking techniques discussed in this paper considers these practical conditions and were evaluated by real data collected from the Yellow Sea, Korea. The proposed method is composed of two parts. In the first part, ship detection, a constant false alarm rate based detector was applied and was enhanced by a PCA subspace decomposition method which reduces noise. To merge multiple detections originated from a single target due to the Doppler effect during long CPIs, a clustering method was applied. Finally, data association framework eliminates false detections by considering ship maneuvering over time. According to evaluation results, it is claimed that the proposed method produces satisfactory results within certain ranges.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.68-73
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• 2005

Various techniques have been proposed for detection and tracking of targets in order to develop a real-world computer vision system, e.g., visual surveillance systems, intelligent transport systems (ITSs), and so forth. Especially, the idea of distributed vision system is required to realize these techniques in a wide-spread area. In this paper, we develop a ubiquitous vision system for location-awareness of multiple targets. Here, each vision sensor that the system is composed of can perform exact segmentation for a target by color and motion information, and visual tracking for multiple targets in real-time. We construct the ubiquitous vision system as the multiagent system by regarding each vision sensor as the agent (the vision agent). Therefore, we solve matching problem for the identity of a target as handover by protocol-based approach. We propose the identified contract net (ICN) protocol for the approach. The ICN protocol not only is independent of the number of vision agents but also doesn't need calibration between vision agents. Therefore, the ICN protocol raises speed, scalability, and modularity of the system. We adapt the ICN protocol in our ubiquitous vision system that we construct in order to make an experiment. Our ubiquitous vision system shows us reliable results and the ICN protocol is successfully operated through several experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1134-1139
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• 2003

Tracking is a fundamental technique which is able to be applied to gesture recognition, visual surveillance, tangible agent and so forth. Especially, multiple object tracking has been extensively studied in recent years in order to perform many and more complicated tasks. In this paper, we propose a new approach of multiple object tracking which is based on discrete event. We call this system the DEMOT (Discrete Event based Multiple Object Tracking). This approach is based on the fact that a multiple object tracking can have just four situations - initiation, continuation, termination, and overlapping. Here, initiation, continuation, termination, and overlapping constitute a primary event set and this is based on the change of the number of extracted objects between a previous frame and a current frame. This system reduces computational costs and holds down the identity of all targets. We make experiments for this system with respect to the number of targets, each event, and processing period. We describe experimental results that show the successful multiple object tracking by using our approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.666-671
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• 2008

In this paper, we propose a new method for tracking objects continously and successively based on fusion of region information, color information and motion template when multiple objects are occluded and splitted. For each frame, color template is updated and compared with the present object. The predicted region, dynamic template and color histogram are used to classify the objects. The vertical histogram of the silhouettes is analyzed to determine whether or not the foreground region contains multiple objects. The proposed method can recognize more correctly the objects to be tracked.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.268-269
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• 2008

Moving object detection is a fundamental technique in visual surveillance. Robust technique to enhance performance of moving object detection is required for several bad conditions in real external circumtance. In case of sudden illumination change in outdoor condition, many objects are determined as moving object though they are not really moving, but just their illumination changes. This makes the detection result untrustworthy. In this paper, robust moving object detection to sudden illumination change using gaussian mixture background model and new texture information using background from the weighted sum of recent images is proposed.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.115-118
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• 2004

Images with high resolution are desired and often required in many visual applications. When resolution can not be improved by replacing sensors, either because of cost or hardware physical limits, super resolution image reconstruction method is what can be resorted to. Super resolution image reconstruction method refers to image processing algorithms that produce high quality and high resolution images from a set of low quality and low resolution images. The method is proved to be useful in many practical cases where multiple frames of the same scene can be obtained, including satellite imaging, video surveillance, video enhancement and restoration, digital mosaicking, and medical imaging. The method can be either the frequency domain approach or the spatial domain approach. Much of the earlier works concentrated on the frequency domain formulation, but as more general degradation models were considered, later researches had been almost exclusively on spatial domain formulations. The method in spatial domains has three stages: i) motion estimate or image registration, ii) interpolation onto high resolution grid and iii) deblurring process. The super resolution grid construction in the second stage was discussed in this paper. We applied the Maximum A­Posteriori(MAP) reconstruction method that is one of the major methods in the super resolution grid construction. Based on this method, we reconstructed high resolution images from a set of low resolution images and compared the results with those from other known interpolation methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1043-1064
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• 2020

A kind of Subjective Imaging Effect Assessment (SIEA) method and its applications on intelligent imaging terminal design in engineering site are presented. First, some visual assessment indices are used to characterize the imaging effect: the image brightness, the image brightness uniformity, the color image contrast, the image edge blur, the image color difference, the image saturation, the image noise, and the integrated imaging effect index. A linear weighted function is employed to carry out the SIEA computation and the Analytic Hierarchy Process (AHP) technique is used to estimate its weights. Second, a SIEA software is developed. It can play images after the settings of assessment index or assessment reaction time, etc. Third, two cases are used to illustrate the application effects of proposed method: the image enhancement system design for surveillance camera and the imaging environment perception system design for intelligent lighting terminal. A Prior Sequential Stimulus (PSS) experiment is proposed to improve the evaluation stability of SIEA method. Many experiment results have shown the proposed method can realize a stable system design or parameters setting for the intelligent imaging terminal in engineering site.

• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.284-288
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• 2010

Video surveillance is widely used in establishing the societal security network. In this paper, intrusion detection based on visual information acquired by static camera is proposed. Proposed approach uses background model constructed by approximated median filter(AMF) to find a foreground candidate, and detected object is calculated by analyzing motion information. Motion detection is determined by the relative size of 2D object in RGB space, finally, the threshold value for detecting object is determined by heuristic method. Experimental results showed that the performance of intrusion detection is better one when the spatio-temporal candidate informations change abruptly.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.3
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• pp.274-282
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• 2011

This paper is focused on dynamic modeling and control system design as well as vision based collision avoidance for multi-rotor unmanned aerial vehicles (UAVs). Multi-rotor UAVs are defined as rotary-winged UAVs with multiple rotors. These multi-rotor UAVs can be utilized in various military situations such as surveillance and reconnaissance. They can also be used for obtaining visual information from steep terrains or disaster sites. In this paper, a quad-rotor model is introduced as well as its control system, which is designed based on a proportional-integral-derivative controller and vision-based collision avoidance control system. Additionally, in order for a UAV to navigate safely in areas such as buildings and offices with a number of obstacles, there must be a collision avoidance algorithm installed in the UAV's hardware, which should include the detection of obstacles, avoidance maneuvering, etc. In this paper, the optical flow method, one of the vision-based collision avoidance techniques, is introduced, and multi-rotor UAV's collision avoidance simulations are described in various virtual environments in order to demonstrate its avoidance performance.