• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2019년도 하계학술대회
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• pp.216-217
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• 2019

Light Field (LF) image can be understood as a set of images captured by a multi-view camera array at the same time. The changes among views can be modeled by a general motion model such as affine motion model. In this paper, we study the impact of affine coding tool of Versatile Video Coding (VVC) on LF image compression. Our experimental results show a small contribution by affine coding tool in overall LF image compression of roughly 0.2% - 0.4%.

• 한국정보과학회논문지:시스템및이론
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• 제37권4호
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• pp.239-245
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• 2010

기존의 회화적 렌더링은 영상 기울기(image gradient) 정보를 사용해 스트로크의 방향, 크기, 길이 등을 결정하였다. 영상 기울기는 객체의 모양을 표현하는데 있어서 유용한 정보이지만 풍경화에서 표현되는 객체(물, 나무 등)의 현재 움직임이나 흐름을 나타낼 수 없는 한계를 가진다. 실제 화가들의 그림에서, 객체의 실제 움직임에 기반한 브러시 스트로크는 관찰자에게 객체의 움직임을 보다 쉽게 인지할 수 있게 하며, 그림이 그려질 당시의 느낌을 보다 생동감 있게 전달할 수 있는 장점을 가진다. 본 논문에서는 풍경화의 주 대상이 되는 객체들의 움직임 정보를 기반으로 동적인 객체의 움직임을 효과적으로 표현할 수 있는 회화적 스트로크 생성에 관한 연구를 제안한다. 이를 위해 동일한 시점을 가진 순차영상 집합으로부터 표현하고자 하는 장면의 움직임 정보(크기, 방향, 편차)을 추출한다. 그리고 움직임의 크기가 큰 영역은 움직임의 방향에 기반하여 스트로크를 생성하며 움직임의 정보가 작은 영역은 영상 기울기 값을 기반으로 방향을 결정한다. 우리의 알고리즘은 사실적인 움직임의 방향을 표현하는데 유용하며 이는 풍경화영상을 렌더링 하는데 유용하다.

• 대한전자공학회논문지SP
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• 제47권2호
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• pp.20-32
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• 2010

기존 모션 캡쳐의 경우, 고가의 장비나 사용의 복잡도, 동작자의 움직임 제한 등 모션 캡쳐의 어려움이 있었다. 최근 실시간으로 모션 캡쳐가 가능한 컴퓨터 비젼 기반 시스템에 대한 연구가 활발히 진행되고 있다. 본 논문에서는 다시점 영상으로부터 쉽고, 빠르게 추출할 수 있는 피부색과 정확한 3차원 복원을 위한 2차원 영상 좌표 보정을 사용하여 효율적인 다시점 영상 분석 알고리즘을 제안한다. 동작자의 피부색을 검출하고, 카메라 보정 및 에피폴라 기하학 정보를 이용하여 보다 정확한 영상 분석, 그라고 칼만 필터(Kalman filter)를 사용한 추적 등을 통해 보다 안정적인 모션 캡쳐가 가능하게 된다. 실험결과를 통하여, 제안된 방법은 보다 정확한 위치 추정 및 살시간 모션 캡쳐를 위한 알고리즘임을 보여주고 있다.

• 한국콘텐츠학회논문지
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• 제7권5호
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• pp.85-93
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• 2007

모션캡쳐시스템은 기존의 키프레임 방식으로는 영상표현이 어려운 인간이나 동물의 사실적인 움직임, 큰 스케일, 많은 경제적 부담이 소요되는 부분 등에 도입되어 새로운 표현 가능성을 보여주고 있다. 또한, 디지털 엔터테인먼트 영역에서 게임을 중심으로 영화, TV, 광고, 다큐멘터리, 뮤직비디오 등 점차 그 활용 빈도가 증가하고 있다. 그러나 이와 같은 장점에도 불구하고 모션캡쳐를 활용한 디지털 영상표현에 있어서 많은 사전준비 작업, 마커의 부착, 모션데이터의 보정, 모션캡쳐 전문 인력 부족 등의 문제점이 대두되고 있다. 이에 본 논문에서 모션캡쳐를 활용한 영상제작 사례 분석을 통하여 보다 효과적인 모션캡쳐 디지털 영상제작의 방향을 제안하고자 한다.

• ETRI Journal
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• 제31권1호
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• pp.1-9
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• 2009

Frequency domain analysis is a fundamental procedure for understanding the characteristics of visual data. Several studies have been conducted with 2D videos, but analysis of stereoscopic 3D videos is rarely carried out. In this paper, we derive the Fourier transform of a simplified 3D video signal and analyze how a 3D video is influenced by disparity and motion in terms of temporal aliasing. It is already known that object motion affects temporal frequency characteristics of a time-varying image sequence. In our analysis, we show that a 3D video is influenced not only by motion but also by disparity. Based on this conclusion, we present a temporal anti-aliasing filter for a 3D video. Since the human process of depth perception mainly determines the quality of a reproduced 3D image, 2D image processing techniques are not directly applicable to 3D images. The analysis presented in this paper will be useful for reducing undesirable visual artifacts in 3D video as well as for assisting the development of relevant technologies.

• 방송공학회논문지
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• 제2권2호
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• pp.125-135
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• 1997

This paper is concerned with realistic mainpulation of content in video sequences. Manipulation of content in video sequences is one of the content-based functionalities for MPEG-4 Visual standard. We present an approach to synthesizing video sequences by using the intermediate outputs of three-dimensional (3D) motion and depth analysis. For concreteness, we focus on video showing 3D motion of an observer relative to a scene containing planar runways (or roads). We first present a simple runway (or road) model. Then, we describe a method of identifying the runway (or road) boundary in the image using the Point of Heading Direction (PHD) which is defined as the image of, the ray along which a camera moves. The 3D motion of the camera is obtained from one of the existing 3D analysis methods. Then, a video sequence containing a runway is manipulated by (i) coloring the scene part above a vanishing line, say blue, to show sky, (ii) filling in the occluded scene parts, and (iii) overlaying the identified runway edges and placing yellow disks in them, simulating lights. Experimental results for a real video sequence are presented.

• 산업기술연구
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• 제21권B호
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• pp.91-98
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• 2001

In this paper, center detection and motion analysis of a moving object are studied. Kohonen's self-organizing neural network models are used for the moving objects tracking and time delay neural networks are used for dynamic characteristic analysis. Instead of objects brightness, neuron projections by Kohonen Networks are used. The motion of target objects can be analyzed by using the differential neuron image between the two projections. The differential neuron image which is made by two consecutive neuron projections is used for center detection and moving objects tracking. The two differential neuron images which are made by three consecutive neuron projections are used for the moving trajectory estimation. It is possible to distinguish 8 directions of a moving trajectory with two frames and 16 directions with three frames.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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• pp.2821-2823
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• 2005

When we deal with the image data through camera lens, much works are necessary for removing image distortions and obtaining accurate informations from the raw data. However, the calibration process is very complicated and requires many trials and errors. In this paper, 3 new approach to image processing is presented by developing a H/W vision system with a tracking camera. Using motor control with encoders the proposed tracking method tells us exact displacements of a moving object. Therefore this method does not require any calibration process for pin cusion. Owing to the mobility one camera covers wide ranges and, by lowering its height, the camera also obtains high resolution of the image. We first introduce the structure of the motion analysis system. Then the construced vision system is investigated by some experiments.

• ETRI Journal
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• 제33권2호
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• pp.259-266
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• 2011

We present a new method for an automated markerless system to describe, analyze, and classify human gait motion. The automated system consists of three stages: I) detection and extraction of the moving human body and its contour from image sequences, ii) extraction of gait figures by the joint angles and body points, and iii) analysis of motion parameters and feature extraction for classifying human gait. A sequential set of 2D stick figures is used to represent the human gait motion, and the features based on motion parameters are determined from the sequence of extracted gait figures. Then, a k-nearest neighbor classifier is used to classify the gait patterns. In experiments, this provides an alternative estimate of biomechanical parameters on a large population of subjects, suggesting that the estimate of variance by marker-based techniques appeared generous. This is a very effective and well-defined representation method for analyzing the gait motion. As such, the markerless approach confirms uniqueness of the gait as earlier studies and encourages further development along these lines.

• 전자공학회논문지B
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• 제32B권6호
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• pp.876-877
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• 1995

The techniques for the estimation of motion vector from the image sequence assume implicitly that the intensity of image is constant through the time. But this assumption can be distored by such causes as the added noises and the sub-pel motion following the sampling, and the errors can be generated on the motion estimation by the change of intensity. In this paper, we analyzed theoretically the effect of the change of intensity by the noise on the motion estimation with the white Gaussian noise. We know a fact that the signal may be fluctuated to reduce the effect of the noise and so the sampling rate have to make down. Also we confirmed the theoretically analysis through the experiments which investigated the relation between the noises and the sampling rates.