• IEIE Transactions on Smart Processing and Computing
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• v.6 no.4
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• pp.237-245
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• 2017

This paper presents a fire detection algorithm using color and motion models from video sequences. The proposed method detects change in color and motion of overall regions for detecting fire, and thus, it can be implemented in both fixed and pan/tilt/zoom (PTZ) cameras. The proposed algorithm consists of three parts. The first part exploits color models of flames and smoke. The candidate regions in the video frames are extracted with the hue-saturation-value (HSV) color model. The second part models the motion information of flames and smoke. Optical flow in the fire candidate region is estimated, and the spatial-temporal distribution of optical flow vectors is analyzed. The final part accumulates the probability of fire in successive video frames, which reduces false-positive errors when fire-like color objects appear. Experimental results from 100 fire videos are shown, where various types of smoke and flames appear in indoor and outdoor environments. According to the experiments and the comparison, the proposed fire detection algorithm works well in various situations, and outperforms the conventional algorithms.

• The Journal of the Korea Contents Association
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• v.2 no.2
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• pp.17-26
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• 2002

In this paper, we suggest a method to acquire the moving object centered video by panning and tilting a camera automatically according to motion vectors calculated by detecting the motion of a moving object on video steam. We create a difference image by estimating the intensity difference at the grid points of neighboring frames. And we detect the motion using both horizontal projection histogram and vertical projection histogram and decide the center of motion part. Then we calculate a new direction and degree of the motion by comparing coordinates at the center of current motion and the center of previous motion. By controling the RCM using these Motion vectors, we can get video stream positioned unwire object on the center of video frame. Through the experiments, we could get a moving object centered video stream continuously arid monitor remotely by implementing sever/client architecture based on the web.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.301-312
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• 2005

Three different cases should be considered for motion tracking: moving object with fixed camera, fixed object with moving camera and moving object with moving camera. Two methods are widely used for motion tracking: the optical flow method and the difference frame method. The optical new method is mainly used when either one, object or camera is fixed. This method tracks object using time-space vector which compares object position frame by frame. This method requires heavy computation, and is not suitable for real-time monitoring system such as DVR(Digital Video Recorder). The different frame method is used for moving object with fixed camera. This method tracks object by comparing the difference between background images. This method is good for real-time applications because computation is small. However, it is not applicable if the camera is moving. This thesis proposes and implements the motion tracking system using the difference frame method with PTZ(Pan-Tilt-Zoom) control. This system can be used for moving object with moving camera. Since the difference frame method is used, the system is suitable for real-time applications such as DVR.

• Journal of the Ergonomics Society of Korea
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• v.31 no.2
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• pp.345-352
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• 2012

Objective: The aim of this study is to evaluate the accuracy and reliability of Spine-Pelvis Monitor(SPM) that was developed to measure 3-dimensional motion of spine and pelvis using tilt sensor and gyro sensor. Background: The main cause of low back pain is very much associated with the task using the low back and pelvis, but no measurement technique can quantify the both spine and pelvis. Method: For testing the SPM, 125 angles from three anatomical planes were measured three times in order to evaluate the accuracy and reliability. The accuracy of SPM in measuring dynamic motion was evaluated using digital motion analysis system. The motion pattern captured by two measuring methods was compared with each other. In result, the percentage error and Cronbach coefficient alpha were calculated to evaluate the accuracy and reliability. Results: The percentage error was 0.35% in flexion-extension on sagittal plane, 0.43% in lateral bending on coronal plane, and 0.40% in twisting on transverse plane. The Cronbach coefficient alpha was 1.00, 0.99 and 0.99 in sagittal, coronal and transvers plane, respectively. Conclusion: The SPM showed less than 1% error for static measurement, and showed reasonably similar pattern with the digital motion system. Application: The results of this study showed that the SPM can be the measuring method of spine pelvis motion that enhances the kinematic analysis of low back dynamics.

• Journal of Sensor Science and Technology
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• v.23 no.6
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• pp.362-367
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• 2014

In this study, a postural change detection sensor module (PCDSM) was developed to detect postural changes in activities of daily living (ADL) and falls. The PCDSM consists of eight mercury sensors that measure angle variations in $360^{\circ}$ rotation and $90^{\circ}$ tilting. From the preliminary study, the output characteristics of the PCDSM were confirmed with the angle variations of rotational motion and a tilting table. Three experiments were conducted to test rotational motion, postural changes, and falling and lying. The results confirmed that the PCDSM could effectively detect postural changes, movement patterns, and falls or non-falls.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.425-428
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• 2000

본 논문에서는 Pan/Tilt 움직임이 있는 카메라 영상에서 실시간으로 이동하는 물체를 검출하고 추적하기 위한 라인매칭(Line-matching)알고리즘을 제안한다. 또한 물체를 추적하기 위해 색상 성분의 분포와 물체의 움직임을 동시에 이용하여 특징 값을 매칭 하는 모션-칼라 매칭(Motion-Color matching)방법을 제안한다. 본 논문에서 제시한 라인매칭 알고리즘은 움직이는 카메라 영상 안에서 움직이는 물체를 추적하는데 있어 효율적으로 카메라의 움직임을 보정하며, 그에 따른 연산 시간도 현저히 줄일 수 있는 방법이다. 실험에 의하면 카메라로부터 입력되는 영상에서 움직임을 검출 추적하는데에 있어 초당 10∼12 frame의 연산 속도를 보였으며, 추적하는 대상에 대하여 배경의 움직임이나 주위의 환경에 영향을 받지 않는 강인한 추적 결과를 보였다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.279-285
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• 1993

This paper presents a precision automatic measuring system for ball screw Pitch. Ball screw is mounted on a precision indexing table, and the ball screw pitch is measured via magnetic scale, where the indexing and measurement are performed by a PC. For precision indexing of ball screw, direct driven motor is coupled to the designed dead and live centers; the performance of the centers are assessed with a precision master sylinder,such as radial motion,tilt motion, and axial motions. An error compensation model is constructed for the measurement system of ball screw pitch, where the error motions of indexing system as well as the scale measurement system are combined to give the measurement error for the ball screw. The developed system proposes an automated precision measurement system for manufacturers and users of ball screw.

• Korean Journal of Hydrosciences
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• v.5
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• pp.115-124
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• 1994

This paper presents the results of a study conducted to improve the understanding of the characteristics of cylindrical capsule flow in a pipeline by taking into account of the effect of capsule density uniformity. The effect fo capsule density variation in the axial direction was studied both experimentally and analytically. The experiments were conducted in a 190mm diameter straight pipe 17m long. The velocity, gap and tilt of capsules were measured under various conditions. In order to interpret the data on various capsule density conditions, the stability index given in the dimensionless number was introduced. The motion of capsules in pipelines is strongly affected by the stability of the capsules characterized by the statility index. The experiments conducted proved that the stability index is a vaild criterion for explaining and correlating data on the capsule motion and the capsule denisity uniformity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.1C
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• pp.47-55
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• 2003

This paper proposes a composition method of mosaic image from the compressed MPEG-2 video stream, in which the displacement between successive frames according to the camera operation is estimated directly from the information involved in the stream. In the proposed method. the approximated optical flow is constructed from motion vectors of macro blocks, and it is used to determine the parameters of the displacements according to the camera operation associated with pan and tilt. The extracted parameters are used to determine the geometric transform of successive video frames in order to construct a mosaic image. The construction of mosaic uses several blending techniques including the one proposed by Nichols in which an analytic weight is used to determine pixel values. Through the experiment, the blending technique based on analytic weights was superior to the others such as averaging and median-based techniques. It provided more smooth changes in background and made use of instantaneous frame information to construct a mosaic. The mosaic in the paper puts the emphasis on the reduction of computation because it is constructed from the motion vectors included in the compressed video without decoding and recalculating exact optical flows. The constructed mosaic can be used in the retrieval of the compressed video as the representative frame of a shot.

• Journal of Broadcast Engineering
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• v.7 no.2
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• pp.181-191
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• 2002

Video based surveillance systems based on an active camera require a fast algorithm for real time detection and tracking of local motion in the presence of global motion. This paper presents a new fast and efficient motion detection and tracking algorithm using the displaced frame difference (DFD). In the Proposed algorithm, first, a Previous frame is adaptively selected according to the magnitude of object motion, and the global motion is estimated by using only a few confident matching blocks for a fast and accurate result. Then, a DFD is obtained between the current frame and the selected previous frame displaced by the global motion. Finally, a moving object is extracted from the noisy DFD by utilizing the correlation between the DFD and current frame. We implement this algorithm into an active camera system including a pan-tilt unit and a standard PC equipped with an AMD 800MHz processor. The system can perform the exhaustive search for a search range of 120, and achieve the processing speed of about 50 frames/sec for video sequences of 320$\times$240. Thereby, it provides satisfactory tracking results.