• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.4
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• pp.787-795
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• 1998

In this paper, we have improved the speed of gradient operation, which needs to calculate Optical Flow for estimating a moving object, and proposed a method which estimate the contour of a moving object by the logical operationg of Optical Flow and edge in noisy images. The proposed method, which recognize to a moving ogject and traking a moving object, using logical operation of Optical Flow and edge in low-level has a advantage that is simpler than the known method for moving objects estimation. In addition, we have simulated several images using method I and method II on improved Gradient operation speed. When we have compared the average value of total operation time, method I is improved with 12% of operation speed compared with the known method, method II is improved with 38% operation speed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.39-49
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• 2002

This paper proposes the MAWUPC (Motion Adaptive Weighted Unmatched Pixel Count) algorithm to track multiple objects of similar color The MAWUPC algorithm has the new method that combines color and motion effectively. We apply the MAWUPC algorithm to face and hand tracking against complex background in an image sequence captured by using single camera. The MAWUPC algorithm is an improvement of previously proposed AWUPC (Adaptive weighted Unmatched Pixel Count) algorithm based on the concept of the Moving Color that combines effectively color and motion information. The proposed algorithm incorporates a color transform for enhancing a specific color, the UPC(Unmatched Pixel Count) operation for detecting motion, and the discrete Kalman filter for reflecting motion. The proposed algorithm has advantages in reducing the bad effect of occlusion among target objects and, at the same time, in rejecting static background objects that have a similar color to tracking objects's color. This paper shows the efficiency of the proposed MAWUPC algorithm by face and hands tracking experiments for several image sequences that have complex backgrounds, face-hand occlusion, and hands crossing.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.117-127
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• 1995

In this paper, we suggest a motion analysis method using ART-I1 competitive learning neural network and fuzzy reasoning by matching the same objects through the consecutive image sequence. we use the size and mean intensity of the region obtained from image segmentation for the region matching by the region and use a ART-I1 competitive learning neural network wh~ch has a learning ability to reflect the topology of the input patterns in order to select characteristic points to describe the shape of a region. Motion vectors for each regions are obtained by matching selected characteristic points. However, the two dimensional image, the projection of the the three dimensional real world, produces fuzziness in motion analysis due to its incompleteness by nature and the error from image segmentation used for extracting information about objects. Therefore, the belief degrees for each regions are calculated using fuzzy reasoning to l-nanipulate uncertainty in motion estimation.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.339-342
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• 2002

동화상 압축에서 사용되는 움직임 벡터는 영상을 일정한 크기의 블록으로 나누어 이전 영상과 가장 예측 오류가 적은 곳을 지정하여 예측한다. 블록의 이동 정도는 수직. 수평의 선형적인 움직임(translational displacements)을 가정하여 사용하기 때문에 실제 화상에서 자주 나타나는 물체의 확대 또는 축소에 의한 크기 변화. 회전. 일그러짐 등의 변화에 올바르게 예측하지 못하는 문제를 가지고 있다. 본 논문은 블록의 선형적인 이동은 물론이고 4개 노드를 자유롭게 움직임일 수 있는 왜곡된 블록 정합 방식의 움직임 예측 기법에 대하여 소개하고 왜곡 블록 정합 방식에서 나타날 수 있는 기하학적인 오류를 수정하는 보정 방법에 관해 논의한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.2043-2052
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• 1997

The object-oriented coding technique which is one of the coding methods in very low bit rate environment is suitable for videophone image sequence. The selection of source model affect image analysis. In this paper, an image analysis method for the object-oriented coding is presented. The process is composed of changed region detection andmotion estimateion. First, we use the standard deviation of frame difference as thrreshold to extract themoving area. If thesum of gray values in mask is greater than the threshold, the center pixel of the mask is regarded as moving region. After moving is detected in changed region by edge operator, observation point is determined from moving region. The motion is estimated by 6-parameter mapping method with determined observation point. The experimantal resutls show that the proposed method can significantly improve the image quality.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2427-2432
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• 2009

This paper proposes an monitoring system of elder and feeble person's motion activity using an object's motion activity data. The proposed system used wireless 3-axis sensor module, product by Freescale(Wireless Sensing Triple Axis Reference Design Board (ZSTAR)). We distribute sensing data into three classes using Neural Network System SVM. We find performance of proposed system that simulate some case about walk, past walk, fallen. Classify result data and graph of sensing data present succes rate 80%.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.553-555
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• 2001

Markov Random Fields(MRF) 모델은 영상 분할 및 복원 등에 주로 사용되는 확률적 영상모델이다. 본 논문에서는 MRF 모델을 3차원으로 확장하여 분할을 위한 선 필드 모델(Line Field Model)과 움직임 검출을 위한 움직임 필드 모델(Motion Field Model)을 도입하여 동영상 내에서 움직이는 물체의 형상과 움직임을 추정한다. 제안된 방법을 이용하여 한국어 수화 동작에서 손의 형상과 이동방향을 검출하였다. 그 결과 optical flow를 사용하는 방법에 비해서 이동 방향이 왜곡되는 것을 방지하여 보다 정확한 이동 방향을 검출할 수 있었다. 또한 영상 추출의 경우에 있어서도 형상의 윤곽면과 내부가 하나의 라벨(label)로 묶이기 때문에 보다 깨끗한 영상을 추출할 수 있었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4C
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• pp.406-412
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• 2003

A fast multiple object motion detection method using periodogram has been proposed. Each frame is projected to vertical and horizontal directions, and then temporal FFT is applied. A line in two dimensional frequency domain indicates velocity. To estimate the velocity of an object, we intergrate along a line which passes through the origin in frequency domain. If a frame contains multiple moving objects, multiple peaks are detected corresponding to the velocity of each object. After pairing these peaks, we can determine the velocities of an object. In the proposal method we can easily pair horizontal and vertical velocity components efficiently with simple computation by combining projections in 45$^{\circ}$ and 135 $^{\circ}$ directions in addition to the vertical and horizontal direction.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.99-104
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• 2002

Existing methods of object tracking use template matching, re-detection of object boundaries or motion information. The template matching method requires very long computation time. The re-detection of object boundaries may produce false edges. The method using motion information shows poor tracking performance in moving camera. In this paper, a robust object tracking algorithm is proposed, using projected motion and histogram intersection. The initial object image is constructed by selecting the regions of interest after image segmentation. From the selected object, the approximate displacement of the object is computed by using 1-dimensional intensity projection in horizontal and vortical direction. Based on the estimated displacement, various template masks are constructed for possible orientations and scales of the object. The best template is selected by using the modified histogram intersection method. The robustness of the proposed tracking algorithm has been verified by experimental results.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04a
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• pp.736-738
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• 2002

본 논문에서는 카메라 이동 및 피사체의 움직임 특성을 이용한 움직인 검출 방식을 제안한다. 카메라 이동 및 피사체의 움직임 특성을 파악하여 움직임을 검출하기 위해 이전 프레임과 현재 프레임 간의 화소 차이의 평균 및 화면 내의 물체의 에지 정보를 이용하여 현재 프레임의 움직임 정도를 판단한다. 그리고 움직임 검출의 정확도를 높이기 위해 화소 차이의 평균을 3단계로 나누어 연산한다. 제안된 움직임 검출 방식은 기존의 움직임 검출 방식에서 나타난 문제점을 보완하며 움직임 검출 범위를 높일 수 있음을 컴퓨터 시뮬레이션을 통해 확인할 수 있었으며, 아남 0.25$\mu$m 공정 라이브러리와 Synopsys 툴을 이용해 VHDL로 구현하였다.