• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.598-600
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• 2002

본 논문에서는 고정된 카메라로부터 입력된 연속 영상에서 움직이는 오브젝트의 영역을 오브젝트의 형태 변화에 덜 민감하게 추적하는 방법을 제안한다. 제안된 방법은 차영상 분석에 의해 오브젝트의 움직임을 감지하는 단계와 연결성 검사 방법을 적응하여 오브젝트의 영역을 찾아내는 단계와 최적 영역 알고리즘을 이용하여 오브젝트에 최적화된 사각의 영역을 구하는 단계로 구성되어져 있다. 제안된 방범을 카메라로부터 입력된 연속영상들을 대상으로 실험해본 결과 오브젝트의 형태변화에 던 민감한 최적영역을 잘 찾아낼 수 있었다

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.123-124
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• 2018

본 논문에서는 HEVC 국제표준으로 압축된 비디오에서 움직임 물체를 추적하는 방법을 제안한다. 제안하는 방법은 HEVC 비트스트림의 대부분을 차지하는 인터 프레임의 움직임 벡터 정보를 입력 데이터로 사용하는 ST-MRF(Spatio-Temporal-Markov Random Field) 모델을 기반으로 하며, ST-MRF 모델에서 발생할 수 있는 오차전파로 점진적으로 객체를 부정확하게 추적하는 것을 HEVC GOP(Group of Picture)마다 삽입되는 인트라 프레임만을 복호화 하여 픽셀 정보를 입력으로 하는 YOLO 모델과 융합시켜 보정함으로써 추적하던 객체를 잃지 않고 강건하게 추적하는 방법을 제안한다.

• Fire Science and Engineering
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• v.32 no.6
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• pp.40-45
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• 2018

The omnidirectional surveillance camera uses the object detection algorithm to level the object by unit so that broadband surveillance can be performed using a fisheye lens and then, it was a field experiment with a system composed of an omnidirectional surveillance camera and a tracking (PTZ) camera. The omnidirectional surveillance camera accurately detects the moving object, displays the squarely, and tracks it in close cooperation with the tracking camera. In the field test of flame detection and temperature of the sensing camera, when the flame is detected during the auto scan, the detection camera stops and the temperature is displayed by moving the corresponding spot part to the central part of the screen. It is also possible to measure the distance of the flame from the distance of 1.5 km, which exceeds the standard of calorific value of 1 km 2,340 kcal. In the performance test of detecting the flame along the distance, it is possible to be 1.5 km in width exceeding $56cm{\times}90cm$ at a distance of 1km, and so it is also adaptable to forest fire. The system is expected to be very useful for safety such as prevention of intrinsic or surrounding fire and intrusion monitoring if it is installed in a petroleum gas storage facility or a storing place for oil in the future.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.1-8
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• 2016

Current indoor intrusion detection and location tracking methods have the weakness in seamless operations in tracking the objective because the object must possess a communicating device and the limitation of the single cell size (approximate $100cm{\times}100cm$) exits. Also, the utilization of CCTV technologies show the shortcomings in tracking when the object disappear the area where the CCTV is not installed or illumination is not enough for capturing the scene (e.g. where the context-awarded system is not installed or low illumination presents). Therefore, in this paper we present an improved in-door tracking system based on sensor networks. Such system is built on a simulated scenario and enables us to detect and extend the area of surveillance as well as actively responding the emergency situation. Through simulated studies, we have demonstrated that the proposed system is capable of supplementing the shortcomings of signal cutting, and of estimating the location of the moving object. We expect the study will improve the better analysis of the intruder behavior, the more effective prevention and flexible response to various emergency situations.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.172-174
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• 2009

This paper describes an implementation method for the 'People Counting System' which detects and tracks moving people using a fixed single camera. This system proposes the method of improving performances by compensating weakness of existing algorithm. For increasing effect of detection, this system uses Single Gaussian Background Modeling which is more robust at noise and has adaptiveness. It minimizes unnecessarily detected area that is a limitation of the detecting method by using the background differences. And this system prevents additional detecting problems by removing shadow. Also, This system solves the problems of segmentation and union of people by using a new method. This method can work appropriately, if the angle of camera would not strictly vertical or the direction of shadow were lopsided. Also, by using integration System, it can solve a number of special cases as many as possible. For example, if the system fails to tracking, it will detect the object again and will make it possible to count moving people.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.8
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• pp.87-95
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• 2007

In this paper, we analyzed the mr detection and the stability of the object tracking system by an adaptive stereo object hacking using region-based MAD(Mean Absolute Difference) algorithm and the modified PID(Proportional Integral Derivative)-based pan/tilt controller. That is, in the proposed system, the location coordinates of the target object in the right and left images are extracted from the sequential stereo input image by applying a region-based MAD algorithm and the configuration parameter of the stereo camera, and then these values could effectively control to pan/tilt of the stereo camera under the noisy circumstances through the modified PID controller. Accordingly, an adaptive control effect of a moving object can be analyzed through the advanced system with the proposed 3D robot vision, in which the possibility of real-time implementation of the robot vision system is also confirmed.

• The Korean Journal of Physiology and Pharmacology
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• v.14 no.6
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• pp.413-417
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• 2010

To understand the function of edges in perception of moving objects, we defined four questions to answer. Is the focus point in visual motion detection of a moving object: (1) the body or the edge of the object, (2) the leading edge or trailing edge of the object, (3) different in scotopic, mesopic and photopic luminance levels, or (4) different for colored objects? We measured the Optomotor Response (OMR) and Edge Triggering Response (ETR) of goldfish. We used a square and sine wave patterns with black and red stripes and a square wave pattern with black and grey stripes to generate OMR's and ETR's in the goldfish. When we used black and red stripes, the black leading edges stimulated an ETR under scotopic conditions, red leading edges stimulated an ETR under photopic conditions, and both black and red leading edges stimulated an ETR under mesopic luminance levels. For black and gray stripes, only black leading edges stimulated an ETR in all three light illumination levels. We observed less OMR and ETR results using the sine wave pattern compared to using the square wave pattern. From these results, we deduced that the goldfish tend to prefer tracking the leading edge of the pattern. The goldfish can also detect the color of the moving pattern under photopic luminance conditions. We decided that ETR is an intriguing factor in OMR, and is suitable as a method of behavioral measurement in visual system research.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.547-554
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• 2013

This paper proposes a novel formation algorithm of identical robots based on object tracking method using omni-directional images obtained through fisheye lenses which are mounted on the robots. Conventional formation methods of multi-robots often use stereo vision system or vision system with reflector instead of general purpose camera which has small angle of view to enlarge view angle of camera. In addition, to make up the lack of image information on the environment, robots share the information on their positions through communication. The proposed system estimates the region of robots using SURF in fisheye images that have $360^{\circ}$ of image information without merging images. The whole system controls formation of robots based on moving directions and velocities of robots which can be obtained by applying Lucas-Kanade Optical Flow Estimation for the estimated region of robots. We confirmed the reliability of the proposed formation control strategy for multi-robots through both simulation and experiment.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.311-316
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• 2009

This paper presents the motion estimation algorithm on real-time for mobile surveillance robot using particle filter. the particle filter that based on the monte carlo's sampling method, use bayesian conditional probability model which having prior distribution probability and posterior distribution probability. However, the initial probability density was set to define randomly in the most of particle filter. In this paper, we find first the initial probability density using Sum of Absolute Difference(SAD). and we applied it in the partical filter. In result, more robust real-time estimation and tracking system on the randomly moving object was realized in the mobile surveillance robot environments.

• ETRI Journal
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• v.38 no.2
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• pp.356-365
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• 2016

This research proposes a modified particle filter to increase the accuracy of vehicle tracking in a noisy and occluded medium. In our proposed method for vehicle tracking, the direction angle of a target vehicle is calculated. The angular difference between the motion direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted depending on their angular distance to the motion direction. Those particles moving in a direction similar to that of the target vehicle are assigned larger weights; this, in turn, increases their probability in a given likelihood function (part of the process of estimation of a target's state parameters). The proposed method is compared against a condensation algorithm. Our results show that the proposed method improves the stability of a particle filter tracker and decreases the particle consumption.