• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.27-33
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• 2009

We propose an efficient method for single image motion deblurring using edge prediction. Previous methods for motion deblurring from a single image have been based on total variation or natural image statistics. In contrast, our method predicts sharp edges by applying bilateral and shock filters and manipulating image gradients directly, and estimates motion blur using the predicted sharp edges. Sharp edge prediction makes our method possible to deblur efficiently with less computation. Results show that our method can effectively and efficiently restore images degraded by large complex motion blur.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1189-1199
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• 2003

This paper presents a new method for the motion detection of vehicles using hierarchical motion estimation and parallel processing. It captures the road image by using a CMOS sensor. It divides the captured image into small blocks and detects the motion of each block by using a block-matching method which is based on a hierarchical motion estimation and parallel processing for the real-time processing. The parallelism is achieved by using tile pipeline and the data flow technique. The proposed method has been implemented by using an embedded system. The proposed block matching algorithm has been implemented on PLDs(Programmable Logic Device) and clustering algorithm has been implemented by ARM processor. Experimental results show that the proposed system detects the motion of vehicles in real-time.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.105-114
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• 2006

In ubiquitous environment where various kinds of computers are embedded in persons, objects and environment and they are interconnected and can be used in my place as necessary, different types of data need to be exchanged between heterogeneous machines through home network. In the environment, the efficient processing, transmission and monitoring of image data are essential technologies. We need to make research not only on traditional image processing such as spatial and visual resolution, color expression and methods of measuring image quality but also on transmission rate on home network that has a limited bandwidth. The present study proposes a new motion vector estimation algorithm for transmitting, processing and controlling image data, which is the core part of contents in home network situation and, using algorithm, implements a real time monitoring system of multi dimensional images transmitted from multiple cameras. Image data of stereo cameras to be transmitted in different environment in angle, distance, etc. are preprocessed through reduction, magnification, shift or correction, and compressed and sent using the proposed metamorphosis hierarchical motion vector estimation algorithm for the correction of motion. The proposed algorithm adopts advantages and complements disadvantages of existing motion vector estimation algorithms such as whole range search, three stage search and hierarchical search, and estimates efficiently the motion of images with high variation of brightness using an atypical small size macro block. The proposed metamorphosis hierarchical motion vector estimation algorithm and implemented image systems can be utilized in various ways in ubiquitous environment.

• Smart Media Journal
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• v.13 no.4
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• pp.16-22
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• 2024

Pitching is a major part of baseball, so much so that it can be said to be the beginning of baseball. Analysis of accurate pitching motions is very important in terms of performance improvement and injury prevention. When analyzing the correct pitching motion, the currently used motion capture method has several critical environmental drawbacks. In this paper, we propose analysis of pitching motion using the RGB-based Human Pose Estimation (HPE) model to replace motion capture, which has these shortcomings, and use motion capture data and HPE data to verify its reliability. The similarity of the two data was verified by comparing joint coordinates using the Dynamic Time Warping (DTW) algorithm.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.4-7
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• 2010

3D 콘텐츠에 대한 관심이 증가함에 따라 3D 시청 및 제작에 대한 가이드라인의 필요성도 함께 증가하고 있다. 3D 안정 시청 가이드 라인은 3D 시청으로 인한 시청자의 시각적 불쾌감이나 피로감을 방지하는데 목적을 두고 있으며, 최근 일본의 3DC에서는 과도한 수렴-조절 불일치를 방지하기 위해 양안 시차 $1^{\circ}$를 쾌적 시차 범위로 권고하고 있다. 하지만 이 쾌적 시차는 절대적인 수치가 아니며, 콘텐츠의 특성 및 시청 조건에 따라 변하는 것으로 추정된다. 본 논문에서는 쾌적 시차를 갖는 3D 영상 콘텐츠에서 객체의 모션으로 인해 양안시차가 시공간적으로 변할 때, 야기되는 시각적 불편함의 변화에 대하여 관찰한다. 특히, 깊이 방향 모션 및 수평 방향 모션에서 객체의 속도 변화에 대한 시각적 피로감의 정도를 주관적 평가를 통하여 측정한다.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05d
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• pp.1093-1098
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• 2002

본 연구실에서 개발한 MIMIC(Motion Interface & Motion Information Capture system)은 동작자의 동작을 획득하고, 동작의 의미를 이해할 수 있도록 설계된 시스템이다. 비전 센서로부터 입력된 영상을 분석하여 동작자의 머리와 두 손, 두 발의 정보를 찾는다. 그리고, 이 정보를 기반으로 팔꿈치나 무릎 등의 중간 관절을 추정한 후 20개의 관절을 가지는 3차원 인체 모델을 구성한다. 이 인체 모델은 동작자의 동작을 실시간으로 흉내낸다. 그러므로, 기존의 마커프리 모션캡쳐 시스템과 달리 완벽한 인체를 구성하기 위한 중간 관절까지 생성함으로써 동작자의 동작을 더욱 자연스럽게 구현할 수 있다.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.2190-2191
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• 2011

지능적인 감시 체계에 대한 필요성이 증대됨에 따라 많은 곳에서 지능화된 군중에 대한 모니터링을 요구하고 있다. 이는 비단 철도 분야에 있어 예외가 되지 않으며, 철도 서비스 구간 내에서의 필요성 또한 증대되고 있다. 철도 승강장 내에는 보안 감시에 사용되는 CCTV가 설치되어 있다. 이렇게 설치되어 있는 CCTV를 통해 철도 승강장의 영상 정보를 취득할 수 있으며 이것을 이용하여 군중 밀도 추정에 도움이 될 수 있다. 본 논문에서는 철도 승강장 내 군중 밀도를 군중의 움직임으로부터 발생되는 모션벡터를 검출하여 군중 밀도와 모션 벡터와의 상관관계에 대해 연구하였다.

• Journal of the Korea Computer Graphics Society
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• v.9 no.3
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• pp.23-29
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• 2003

There is the temporal correlation of the video sequence between the motion vector of current block and the motion vector of the previous block. If we can obtain useful and enough information from the motion vector of the same coordinate block of the previous frame, the total number of search points used to find the motion vector of the current block may be reduced significantly. In this paper, we propose the block-matching motion estimation using an adaptive initial search point by the predicted motion information from the same block of the previous frame. And the first search point of the proposed algorithm is moved an initial point on the location of being possibility and the searching process after moving the first search point is processed according to the fast search pattern. Simulation results show that PSNR(Peak-to-Signal Noise Ratio) values are improved UP to the 1.05dB as depend on the image sequences and improved about 0.33~0.37dB on an average. Search times are reduced about 29~97% than the other fast search algorithms. Simulation results also show that the performance of the proposed scheme gives better subjective picture quality than the other fast search algorithms and is closer to that of the FS(Full Search) algorithm.

• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.405-417
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• 2020

Due to the popularization of the Extended Reality, research is actively underway to implement human motion in real-time 3D animation. In particular, Microsoft developed Kinect cameras for 3D motion information can be obtained without the burden of facilities and with simple operation, real-time animation can be generated by combining with 3D formats such as FBX. Compared to the marker-based motion capture system, however, Kinect has low accuracy due to its lack of estimated performance of joint information. In this paper, two algorithms are proposed to correct joint estimation errors in order to realize natural human motion in motion capture animation system in Kinect camera-based FBX format. First, obtain the position information of a person with a Kinect and create a depth map to correct the wrong joint position value using the human body segment length constraint information, and estimate the new rotation value. Second, the pre-set joint motion range constraint is applied to the existing and estimated rotation value and implemented in FBX to eliminate abnormal behavior. From the experiment, we found improvements in human behavior and compared errors between algorithms to demonstrate the superiority of the system.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.20-32
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• 2010

Previous hardware devices to capture human motion have many limitations; expensive equipment, complexity of manipulation or constraints of human motion. In order to overcome these problems, real-time motion capture algorithms based on computer vision have been actively proposed. This paper presents an efficient analysis method of multiple view images for real-time motion capture. First, we detect the skin color regions of human being, and then correct the image coordinates of the regions by using camera calibration and epipolar geometry. Finally, we track the human body part and capture human motion using kalman filter. Experimental results show that the proposed algorithm can estimate a precise position of the human body.