• The KIPS Transactions:PartB
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• v.15B no.1
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• pp.9-16
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• 2008

In this paper, we present an algorithm for synthesizing intermediate view image from a stereoscopic pair of images. An image of multiview is need for people in order to easily recognize 3D image. However, if many cameras are use for that, not only does system get more complicated but also transmission rating cause a big trouble. Hence, stereo images are photograph and issue on the sending side and algorithm to generate several intermediate view image is able to be use on the receiving side. The proposed method is based on disparity space image. First of all, disparity space image that is depicted by the gap of pixel followed by disparity of stereo image is generated. Disparity map is made by utilizing disparity space image for searching for optimal disparity path then eventual intermediate view image is generated after occlusion region which does not match is processed. Experimental results illustrate the performance of the proposed technique and we obtained a high quality image of more than 30 dB PSNR.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2343-2352
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• 2015

In this paper, we propose novel motion field estimation method using U-disparity map and forward-backward error removal in vehicles environment. Generally, in an image obtained from a camera attached in a vehicle, a motion vector occurs according to the movement of the vehicle. but this motion vector is less accurate by effect of surrounding environment. In particular, it is difficult to extract an accurate motion vector because of adjacent pixels which are similar each other on the road surface. Therefore, proposed method removes road surface by using U-disparity map and performs optical flow about remaining portion. forward-backward error removal method is used to improve the accuracy of the motion vector. Finally, we predict motion of the vehicle by applying RANSAC(RANdom SAmple Consensus) from acquired motion vector and then generate motion field. Through experimental results, we show that the proposed algorithm performs better than old schemes.

• Journal of the Korea Society of Computer and Information
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• v.19 no.7
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• pp.17-25
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• 2014

In the devices that leave video records, it is an important issue to distinguish whether the input image is a real object or a photo when securing an identifying image. Using a single image and sensor, which is a simple way to distinguish the target from distance measurement has many weaknesses. Thus, this paper proposes a way to distinguish a simple photo and a real object by using stereo images. It is not only measures the distance to the target, but also checks a three-dimensional effect by making the depth map of the face area. They take pictures of the photos and the real faces, and the measured value of the depth map is applied to the learning algorithm. Exactly through iterative learning to distinguish between the real faces and the photos looked for patterns. The usefulness of the proposed algorithm was verified experimentally.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.359-366
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• 2003

We propose a real-time stereoscopic image conversion method that can generate stereoscopic image with different perspective depth using motion parallax from 2-D image and offer realistic 3-D effect regardless of the direction and velocity of the moving object in the 2-D image. The stereoscopic image is generated by computing the motion parallax between adjacent two 2-D images using the proposed method for motion detection, region segmentation and depth map generation. The proposed method is suitable for real-time stereoscopic conversion processing on various image formats. It has been verified the proposed method by comparing between the stereoscopic image of the proposed method and that of MTD.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.995-996
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• 2008

This paper proposes a algorithm that generate the intermediate scene from the stereo image. This system based on mesh representation method, and segmented objects which ar calculated from triangles the pro proposed algorithm is composed of two steps. One is triangle grouping using gestalt theory, and the other is disparity estimation using average disparity of segmented object. We make an experiment on the proposed algorithm with some stereo images and obtain good quality disparity map for intermediate scenes.

• Journal of Digital Contents Society
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• v.6 no.3
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• pp.157-162
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• 2005

In this paper we propose real-time cocersion methods that can convert into stereoscopic image using depth map that is formed by motion detection extracted from 2-D moving image and region segmentation separated from image. Depth map which represents depth information of image and the proposed absolute parallax image are used as the measure of qualitative evaluation. We have compared depth information, parallax processing, and segmentation between objects with different depth for proposed and conventional method. As a result, we have confirmed the proposed method can offer realistic stereoscopic effect regardless of direction and velocity of moving object for a moving image.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.367-369
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• 2006

사람은 일반적으로 깊이를 지각하는데 두 눈으로 들어오는 영상의 시차(binocular disparity)를 이용하며 6-15m 정도의 범위 내에서는 매우 뛰어난 깊이 판별 능력을 보인다. 그러나 사람은 하나의 눈만으로도 깊이를 지각하는데 별 어려움을 느끼지 못한다. 이것은 공간의 깊이 지각 단서로 양안단서안이 아니라 다양한 단안단서(monocular Cue)들이 함께 사용되기 때문이다. 본 논문에서는 사람이 공간 깊이정보 파악에 사용하는 것으로 알려진 여러 단안 단서들 중 영상의 채도(saturation) 정보와 디포커스(defocus) 정보, 기하학적 깊이(geometric depth) 정보에 기반을 둔 단안 영상에서의 상대적 깊이지도의 생성방법을 제안한다.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.115-121
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• 2017

In this paper, the intelligent vision system for an effective and intelligent path-planning of an industrial AGV system based on stereo camera system is proposed. The depth information and disparity map are detected in the inputting images of a parallel stereo camera. The distance between the industrial AGV system and the obstacle detected and the 2D path coordinates obtained from the location coordinates, and then the relative distance between the obstacle and the other objects obtained from them. The industrial AGV system move automatically by effective and intelligent path-planning using the obtained 2D path coordinates. From some experiments on AGV system driving with the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the objects is found to be very low value of 2% on average, respectably.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.347-352
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• 2012

In this paper, an 2D spatial-map construction for workers identification and avoidance of AGV using the detection scheme of the spatial coordinates based on stereo camera is proposed. In the proposed system, face area of a moving person is detected from a left image among the stereo image pairs by using the YCbCr color model and its center coordinates are computed by using the centroid method and then using these data, the stereo camera embedded on the mobile robot can be controlled for tracking the moving target in real-time. Moreover, using the disparity map obtained from the left and right images captured by the tracking-controlled stereo camera system and the perspective transformation between a 3-D scene and an image plane, depth map can be detected. From some experiments on AGV driving with 240 frames of the stereo images, it is analyzed that error ratio between the calculated and measured values of the worker's width is found to be very low value of 2.19% and 1.52% on average.

• 전자공학회논문지 IE
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• v.46 no.1
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• pp.23-30
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• 2009

In this paper, the intelligent vision system for an effective and intelligent path-planning of an industrial AGV system based on stereo camera system is proposed. The depth information and disparity map are detected in the inputting images of a parallel stereo camera. The distance between the industrial AGV system and the obstacle detected and the 2D Path coordinates obtained from the location coordinates, and then the relative distance between the obstacle and the other objects obtained from them. The industrial AGV system move automatically by effective and intelligent path-planning using the obtained 2D path coordinates. From some experiments on AGV system driving with the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the objects is found to be very low value of 2.5% on average, respectably.