• 제목/요약/키워드: depth image-based

검색결과 821건 처리시간 0.029초

깊이영상의 전처리를 이용한 다시점 영상 생성 방법 (Multi-view Image Generation by Depth Map Preprocessing)

  • 이상범;김성열;호요성
    • 대한전자공학회:학술대회논문집
    • /
    • 대한전자공학회 2006년도 하계종합학술대회
    • /
    • pp.697-698
    • /
    • 2006
  • In this paper, we propose a new scheme to generate multi-view images using a depth-image-based rendering (DIBR) technique. In order to improve the quality of multi-view images at newly exposed areas during mesh-based rendering, we preprocess the depth map using a Gaussian smoothing filter. Previous algorithms apply a smoothing filter to the whole depth map even if the depth map is collapsed. After extracting objects from the depth map, we apply the smoothing filter to their boundaries. Finally, we cannot only maintain the depth quality, but also generate high quality multi-view images. Experimental results show that our proposed algorithm outperforms previous works and supports an efficient depth keying technique.

  • PDF

스테레오 비젼에 기반한 6축 로봇의 위치 결정에 관한 연구 (Position Control of Robot Manipulator based on stereo vision system)

  • 조환진;박광호;기창두
    • 한국정밀공학회:학술대회논문집
    • /
    • 한국정밀공학회 2001년도 춘계학술대회 논문집
    • /
    • pp.590-593
    • /
    • 2001
  • In this paper we describe the 6-axes robot's position determination using a stereo vision and an image based control method. When use a stereo vision, it need a additional time to compare with mono vision system. So to reduce the time required, we use the stereo vision not image Jacobian matrix estimation but depth estimation. Image based control is not needed the high-precision of camera calibration by using a image Jacobian. The experiment is executed as devide by two part. The first is depth estimation by stereo vision and the second is robot manipulator's positioning.

  • PDF

GPU를 이용한 특징 기반 영상모핑의 가속화 (Acceleration of Feature-Based Image Morphing Using GPU)

  • 김은지;윤승현;이지은
    • 한국컴퓨터그래픽스학회논문지
    • /
    • 제20권2호
    • /
    • pp.13-24
    • /
    • 2014
  • 본 논문에서는 특징 기반 영상모핑(feature-based image morphing)을 위한 GPU (Graphics Processing Unit) 기반의 가속화 기법을 제시한다. 제안된 기법은 모핑과정에서 픽셀과 제어선 사이의 최단거리를 효율적으로 계산하기 위해 그래픽스 하드웨어의 깊이 버퍼(depth-buffer)를 이용한다. 먼저 원본영상(source image)과 최종영상(destination image)에 사용자입력을 통해 특징을 표현하는 제어선들을 지정하고, 각 제어선의 거리함수(distance function)를 서로 다른 색상을 갖는 두개의 사각형과 원뿔로 렌더링한다. 그래픽스 파이프라인(graphics pipeline)을 통해 각 픽셀에서 가장 가까운 제어선까지의 거리는 깊이 버퍼에 저장되고, 이는 모핑연산을 효율적으로 수행하는데 사용된다. 본 논문에서는 픽셀 단위의 모핑 연산을 CUDA(Compute Unified Device Architecture)를 이용하여 병렬화함으로써 모핑의 속도를 더욱 향상시키며, 다양한 크기의 입력영상에 대하여 각각 CPU와 GPU를 이용한 영상모핑 실험을 통해 제안된 기법의 효율성을 입증한다.

모션 추정과 객체 추적을 이용한 이미지 깊이 검출기법 (A Technique of Image Depth Detection Using Motion Estimation and Object Tracking)

  • 조범석;김영로
    • 디지털산업정보학회논문지
    • /
    • 제4권2호
    • /
    • pp.15-19
    • /
    • 2008
  • In this paper, we propose a new algorithm of image depth detection using motion estimation and object tracking. In industry, robots are used for automobile, conveyer system, etc. But, these have much necessary time. Thus, in this paper, we develop the efficient method of image depth detection based on motion estimation and object tracking.

깊이 영상을 이용한 3D 프린팅 기반 환자 맞춤형 안와 임플란트의 설계 및 제작 (3D Printing Based Patient-specific Orbital Implant Design and Production by Using A Depth Image)

  • 서우덕;김구진
    • 한국멀티미디어학회논문지
    • /
    • 제23권8호
    • /
    • pp.903-914
    • /
    • 2020
  • In this paper, we present a novel algorithm to generate a 3D model of patient-specific orbital implant, which is finally produced by the 3D printer. Given CT (computed tomography) scan data of the defective orbital wall or floor, we compose the depth image of the defect site by using the depth buffering, which is a computer graphics technology. From the depth image, we compute the 3D surface which fills the broken part by interpolating the points around the broken part. By thickening the 3D surface, we get the 3D volume mesh of the orbital implant. Our algorithm generates the patient-specific orbital implant whose shape is accurately coincident to the broken part of the orbit. It provides the significant time efficiency for manufacturing the implant with supporting high user convenience.

2차원 동영상의 3차원 변환을 위한 깊이 단서의 신뢰성 기반 적응적 깊이 융합 (Adaptive Depth Fusion based on Reliability of Depth Cues for 2D-to-3D Video Conversion)

  • 한찬희;최해철;이시웅
    • 한국콘텐츠학회논문지
    • /
    • 제12권12호
    • /
    • pp.1-13
    • /
    • 2012
  • 3차원 동영상은 다양한 응용분야들에서 차세대 콘텐츠로 큰 주목을 받고 있다. 2D-to-3D 변환은 3차원 동영상의 시대로 넘어가는 과도기 동안에 3차원 동영상 콘텐츠의 부족현상을 해결하기위한 강력한 기술로 여겨지고 있다. 일반적으로 2D-to-3D 변환을 위해서는 2차원 동영상 각 장면의 깊이영상을 추정/생성한 후 깊이 영상 기반 랜더링 (DIBR : Depth Image Based Rendering) 기술을 이용하여 스테레오 동영상을 합성한다. 본 논문은 2차원 동영상 내 존재하는 다양한 변환 단서들을 통합하는 새로운 깊이 융합 기법을 제안한다. 우선, 알맞은 깊이 융합을 위해 몇몇 단서가 현재 장면을 효과적으로 표현할 수 있는 지 아닌지 검사된다. 그 후, 신뢰성 검사의 결과를 기반으로 현재 장면은 4개의 유형 중 하나로 분류된다. 마지막으로 최종 깊이 영상을 생성하기 위해 신뢰할 수 있는 깊이 단서들을 조합하는 장면 적응적 깊이 융합이 수행된다. 실험 결과를 통해 각각의 단서가 장면 유형에 따라 타당하게 활용되었고 최종 깊이 영상이 현재 장면을 효과적으로 표현할 수 있는 단서들에 의해 생성되었음을 관찰할 수 있다.

Computational Approach to Color Overlapped Integral Imaging for Depth Estimation

  • Lee, Eunsung;Lim, Joohyun;Kim, Sangjin;Har, Donghwan;Paik, Joonki
    • IEIE Transactions on Smart Processing and Computing
    • /
    • 제3권6호
    • /
    • pp.382-387
    • /
    • 2014
  • A computational approach to depth estimations using a color over lapped integral imaging system is presented. The proposed imaging system acquires multiple color images simultaneously through a single lens with an array of multiple pinholes that are distributed around the optical axis. This paper proposes a computational model of the relationship between the real distance of an object and the disparity among different color images. The proposed model can serve as a computational basis of a single camera-based depth estimation.

Algorithms to measure carbonation depth in concrete structures sprayed with a phenolphthalein solution

  • Ruiz, Christian C.;Caballero, Jose L.;Martinez, Juan H.;Aperador, Willian A.
    • Advances in concrete construction
    • /
    • 제9권3호
    • /
    • pp.257-265
    • /
    • 2020
  • Many failures of concrete structures are related to steel corrosion. For this reason, it is important to recognize how the carbonation can affect the durability of reinforced concrete structures. The repeatability of the carbonation depth measure in a specimen of concrete sprayed with a phenolphthalein solution is consistently low whereby it is necessary to have an impartial method to measure the carbonation depth. This study presents two automatic algorithms to detect the non-carbonated zone in concrete specimens. The first algorithm is based solely on digital processing image (DPI), mainly morphological and threshold techniques. The second algorithm is based on artificial intelligence, more specifically on an array of Kohonen networks, but also using some DPI techniques to refine the results. Moreover, another algorithm was developed with the purpose of measure the carbonation depth from the image obtained previously.

Color-Image Guided Depth Map Super-Resolution Based on Iterative Depth Feature Enhancement

  • Lijun Zhao;Ke Wang;Jinjing, Zhang;Jialong Zhang;Anhong Wang
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제17권8호
    • /
    • pp.2068-2082
    • /
    • 2023
  • With the rapid development of deep learning, Depth Map Super-Resolution (DMSR) method has achieved more advanced performances. However, when the upsampling rate is very large, it is difficult to capture the structural consistency between color features and depth features by these DMSR methods. Therefore, we propose a color-image guided DMSR method based on iterative depth feature enhancement. Considering the feature difference between high-quality color features and low-quality depth features, we propose to decompose the depth features into High-Frequency (HF) and Low-Frequency (LF) components. Due to structural homogeneity of depth HF components and HF color features, only HF color features are used to enhance the depth HF features without using the LF color features. Before the HF and LF depth feature decomposition, the LF component of the previous depth decomposition and the updated HF component are combined together. After decomposing and reorganizing recursively-updated features, we combine all the depth LF features with the final updated depth HF features to obtain the enhanced-depth features. Next, the enhanced-depth features are input into the multistage depth map fusion reconstruction block, in which the cross enhancement module is introduced into the reconstruction block to fully mine the spatial correlation of depth map by interleaving various features between different convolution groups. Experimental results can show that the two objective assessments of root mean square error and mean absolute deviation of the proposed method are superior to those of many latest DMSR methods.

Hole-Filling Methods Using Depth and Color Information for Generating Multiview Images

  • Nam, Seung-Woo;Jang, Kyung-Ho;Ban, Yun-Ji;Kim, Hye-Sun;Chien, Sung-Il
    • ETRI Journal
    • /
    • 제38권5호
    • /
    • pp.996-1007
    • /
    • 2016
  • This paper presents new hole-filling methods for generating multiview images by using depth image based rendering (DIBR). Holes appear in a depth image captured from 3D sensors and in the multiview images rendered by DIBR. The holes are often found around the background regions of the images because the background is prone to occlusions by the foreground objects. Background-oriented priority and gradient-oriented priority are also introduced to find the order of hole-filling after the DIBR process. In addition, to obtain a sample to fill the hole region, we propose the fusing of depth and color information to obtain a weighted sum of two patches for the depth (or rendered depth) images and a new distance measure to find the best-matched patch for the rendered color images. The conventional method produces jagged edges and a blurry phenomenon in the final results, whereas the proposed method can minimize them, which is quite important for high fidelity in stereo imaging. The experimental results show that, by reducing these errors, the proposed methods can significantly improve the hole-filling quality in the multiview images generated.