• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.5-7
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• 1996

We propose a triangulation method based on stereo vision angles. We setup stereo vision systems which extract the depth information to a moving object by detecting a moving object using difference image method and obtaining the depth information by the triangulation method based on stereo vision angles. The feature point of a moving object is used the geometrical center of the moving object, and the proposed vision system has the accuracy of 0.2mm in the range of 400mm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.181.5-181
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• 2001

This paper presents the method of 3D reconstruction of the depth information from the endoscopic stereo scopic images. After camera modeling to find camera parameters, we performed feature-point based stereo matching to find depth information. Acquired some depth information is finally 3D reconstructed using the NURBS(Non Uniform Rational B-Spline) algorithm. The final result image is helpful for the understanding of depth information visually.

• 정보처리학회논문지B
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• 제8B권5호
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• pp.549-556
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• 2001

2차원 영상으로 부터 3차원 영상으로 복원하는 일은 일반적으로 카메라의 초점에서 영상 프레임의 각 픽셀까지의 깊이 정보가 필요하고, 3차원 모델의 복원에 관한 일반적인 수작업은 많은 식나과 비용이 소모된다. 본 논문에서는 카메라의 움직임이 포함되어 있는 단안 영상 시퀸스로부터 3차원 영상 제작에 필요한 상대적인 깊이 정보를 실시간으로 추출하는 알고리즘을 제안하고, 하드웨어를 구현하기 위한여 알고리즘을 단순화하였다. 이 알고리즘은 카메라 이동에 의한 영상의 모든 점들의 움직임은 깊이 정보의 종속적이라는 사실에 기반을 두고 있다. 불록매칭 알고리즘에 기반을 둔 전역 움직임 탐색에 의한 움직임 벡터를 추출한 후, 카메라 회전과 확대/축소에 관한 카메라 움직임 보상을 실행하고 깉이 정보 추출 과정이 전개된다. 깊이 정보 추출 과정은 단안 영상에서 객체의 이동처리를 분석하여 움직임 벡터를 구하고 프레임내의 모든 픽셀에 대한 평균 깊이를 계산한 후, 평균 깊이에 대한 각 블록의 상대적 깊이를 산출하였다. 모의 실험 결과 전경과 배경에 속하는 영역의 깊이는 인간 시각 체계가 인식하는 상대적인 깊이와 일치한다는 것을 보였다.

• International Journal of Internet, Broadcasting and Communication
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• 제7권1호
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• pp.15-19
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• 2015

The depth information of an image is used in a variety of applications including 2D/3D conversion, multi-view extraction, modeling, depth keying, etc. There are various methods to acquire depth information, such as the method to use a stereo camera, the method to use the depth camera of flight time (TOF) method, the method to use 3D modeling software, the method to use 3D scanner and the method to use a structured light just like Microsoft's Kinect. In particular, the depth camera of TOF method measures the distance using infrared light, whereas TOF sensor depends on the sensitivity of optical light of an image sensor (CCD/CMOS). Thus, it is mandatory for the existing image sensors to get an infrared light image by bundling several pixels; these requirements generate a phenomenon to reduce the resolution of an image. This thesis proposed a measure to acquire a high-resolution image through gradual area movement while acquiring a low-resolution image through pixel bundling method. From this measure, one can obtain an effect of acquiring image information in which illumination intensity (lux) and resolution were improved without increasing the performance of an image sensor since the image resolution is not improved as resolving a low-illumination intensity (lux) in accordance with the gradual pixel bundling algorithm.

• 한국통신학회논문지
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• 제34권12C호
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• pp.1147-1153
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• 2009

본 논문에서는 분할 영역기반 스테레오 정합에 있어서 분할 영역 추출시 컬러 외에 깊이 카메라의 초기 깊이, 프레임 간 분할 영역의 움직임 정보를 같이 이용한 분할 영역기반 스테레오 정합 기법을 제안한다. 제안한 기법은 깊이 카메라의 초기 깊이 정보를 이용하여 기준 영상의 객체/배경 분리를 먼저 수행하고, 분리된 객체/배경별로 컬러 영상 분할을 수행하여 분할 영역을 추출한다. 또한 분할 영역기반 깊이 정보 추출에 있어 프레임 간 깊이 정보의 연속성을 유지하기 위해 객체/배경 분리 정보, 분할 영역의 움직임 정보를 이용한다. 실험결과에서, 제안한 기법은 컬러 정보만을 이용한 기존의 분할 영역 추출 및 분할 영역 기반 스테레오 정합 기법에 비해 정적배경 영역에서 특히 분할 영역 추출과 깊이 정확도가 개선된 성능을 보였다.

• 한국멀티미디어학회논문지
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• 제19권10호
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• pp.1767-1774
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• 2016

In this paper, we propose the adaptation filtering for correcting the movement path of the recognized object by the depth information. When we recognize the object by the depth information, the path error should be occurred because of the noises in the depth information. The path error is corrected by appling the lowpass filtering, but the lowpass filtering is not efficient when the changes of the object's movement are rapid. In this paper, we apply the adaptation filtering that it gives weights adaptively as the difference between the predicted location and the measured location. To apply the adaptation filtering, we can see that the proposed method can correct accurately the path error of the radical change from simulation results.

• 한국멀티미디어학회논문지
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• 제21권2호
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• pp.138-146
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• 2018

In this paper, we describe an algorithm for extracting depth information from a single image based on CNN. When acquiring three-dimensional information from a single two-dimensional image using a deep-learning technique, it is difficult to accurately predict the edge portion of the depth image because it is a part where the depth changes abruptly. in this paper, we introduce the concept of pixel-wise confidence to take advantage of these characteristics. We propose an algorithm that estimates depth information from a highly reliable flat part and propagates it to the edge part to improve the accuracy of depth estimation.

• 반도체디스플레이기술학회지
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• 제21권4호
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• pp.77-80
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• 2022

Automatic Vision Inspection (AVI) systems automatically detect defect features and measure their sizes via camera vision. It has been populated because of the accuracy and consistency in terms of QC (Quality Control) of inspection processes. Also, it is important to predict the performance of an AVI to meet customer's specification in advance. AVI are usually suffered from false negative and positives. It can be overcome by providing extra information such as 3D depth information. Stereo vision processing has been popular for depth extraction of the 3D images from 2D images. However, stereo vision methods usually take long time to process. In this paper, retro optical system using reflectors is proposed and experimented to overcome the problem. The optical system extracts the depth without special SW processes. The vision sensor and optical components such as illumination and depth detecting module are integrated as a unit. The depth information can be extracted on real-time basis and utilized and can improve the performance of an AVI system.

• Journal of information and communication convergence engineering
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• 제12권2호
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• pp.122-127
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• 2014

This paper proposes a method to manipulate digital hologram contents by manipulating and/or synthesizing the depth information. To synthesize digital holograms themselves in order to create new digital hologram contents. This paper uses both the depth information obtained by converting the disparity information by using a stereo matching method and that obtained by taking pictures with a depth camera. In addition, assuming that digital holograms are created using the computer-generated holography method, we propose a technique for authoring and compositing hologram contents by using either the changes in the three-dimensional positions of objects in the hologram or by combining the objects with other contents by means of changes in the depth information. Further, more than one digital hologram was synthesized to form a hologram. The reconstructed result from the synthesized hologram also contained all the objects in each digital hologram before synthesis at the same positions and distances.

• Journal of Information Processing Systems
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• 제19권4호
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• pp.483-497
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• 2023

Depth estimation is one of the most complicated and difficult problems to deal with in the light field. In this paper, a compound attention convolutional neural network (CAttNet) is proposed to extract depth maps from light field images. To make more effective use of the sub-aperture images (SAIs) of light field and reduce the redundancy in SAIs, we use a compound attention mechanism to weigh the channel and space of the feature map after extracting the primary features, so it can more efficiently select the required view and the important area within the view. We modified various layers of feature extraction to make it more efficient and useful to extract features without adding parameters. By exploring the characteristics of light field, we increased the network depth and optimized the network structure to reduce the adverse impact of this change. CAttNet can efficiently utilize different SAIs correlations and features to generate a high-quality light field depth map. The experimental results show that CAttNet has advantages in both accuracy and time.