• 로봇학회논문지
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• 제4권4호
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• pp.298-304
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• 2009

This paper describes an algorithm that improves 3D reconstruction result using a multi-sensor fusion disparity map. We can project LRF (Laser Range Finder) 3D points onto image pixel coordinatesusing extrinsic calibration matrixes of a camera-LRF (${\Phi}$, ${\Delta}$) and a camera calibration matrix (K). The LRF disparity map can be generated by interpolating projected LRF points. In the stereo reconstruction, we can compensate invalid points caused by repeated pattern and textureless region using the LRF disparity map. The result disparity map of compensation process is the multi-sensor fusion disparity map. We can refine the multi-sensor 3D reconstruction based on stereo vision and LRF using the multi-sensor fusion disparity map. The refinement algorithm of multi-sensor based 3D reconstruction is specified in four subsections dealing with virtual LRF stereo image generation, LRF disparity map generation, multi-sensor fusion disparity map generation, and 3D reconstruction process. It has been tested by synchronized stereo image pair and LRF 3D scan data.

• Journal of information and communication convergence engineering
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• 제13권4호
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• pp.275-279
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• 2015

There are several methods to record three dimensional (3D) information of objects such as lens array based integral imaging, synthetic aperture integral imaging (SAII), computer synthesized integral imaging (CSII), axially distributed image sensing (ADS), and axially distributed stereo image sensing (ADSS). ADSS method is capable of recording partially occluded 3D objects and reconstructing high-resolution slice plane images. In this paper, we present a computational method for depth extraction of partially occluded 3D objects using ADSS. In the proposed method, the high resolution elemental stereo image pairs are recorded by simply moving the stereo camera along the optical axis and the recorded elemental image pairs are used to reconstruct 3D slice images using the computational reconstruction algorithm. To extract depth information of partially occluded 3D object, we utilize the edge enhancement and simple block matching algorithm between two reconstructed slice image pair. To demonstrate the proposed method, we carry out the preliminary experiments and the results are presented.

• 방송공학회논문지
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• 제24권6호
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• pp.1064-1071
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• 2019

다중뷰 스테레오 정합 알고리즘은 시점이 다른 복수의 2차원 영상으로부터 3차원 형상을 복원하기 위해 사용된다. 기존의 다중뷰 스테레오 정합 알고리즘은 단계별로 많은 계산량을 포함하는 복잡한 구조 때문에 고성능 하드웨어에서만 주로 구현되어왔다. 그러나 최근에 모바일 그래픽 프로세서가 발전하면서 충분한 부동소수점 계산 성능이 확보됨에 따라 기존의 PC 환경에서만 수행되었던 복잡한 컴퓨터 비전 알고리즘들이 모바일 GPU에서 구현되고 있다. 본 논문에서는 임베디드 보드의 모바일 GPU에서의 병렬처리를 기반으로 다중뷰 스테레오 알고리즘의 병렬처리를 구현하고 자원이 제한적인 하드웨어에서의 성능 최적화 기법을 제안한다.

• 정보처리학회논문지B
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• 제12B권4호
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• pp.429-436
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• 2005

본 논문에서는 유전자 알고리즘의 일반적인 문제점인 과도한 저장공간의 소모와 탐색의 비효율성을 줄이기 위해 PBIL을 이용한 단순한 스테레오 정합 기법을 제안한다. PBIL은 확률벡터에 기반해서 통계적 탐색과 경쟁학습을 이용하는 변종 유전자 알고리즘이며 확률벡터의 사용으로 인해 직렬 및 병렬 유전자 알고리즘군에 비해 단순한 구조를 가진다. 본 논문에서는 이 PBIL을 스테레오 정합 환경에 맞게 변형 및 단순화시켜 정합 알고리즘을 개발한다. 높은 적응성을 갖는 염색체는 생존 확률 또한 높다는 진화 법칙을 보존하면서 유전자 풀, 염색체 교차 및 유전자 돌연변이를 제거할 수 있으며 그 결과 저장공간을 줄이고 정합 규칙을 간소화하여 계산 비용을 감소시킬 수 있다. 추가적으로 다해상도 정합 기법처럼 넓은 영역의 변이 일관성을 획득하기 위해 변이 연속성에 대한 이웃들의 거리를 제어하는 방식을 추가하여 고정된 작은 정합창을 사용하면서 안정된 결과를 얻을 수 있게 한다. 마지막으로 단순한 시스템에 적용될 수 있게 하기 위해서 확률벡터를 사용하지 않는 제안한 알고리즘의 소형 대안 기법을 제시한다.

• 디지털산업정보학회논문지
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• 제8권2호
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• pp.95-104
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• 2012

In this paper, an estimation of person height and 3D location of a moving person by using the pan/tilt-embedded stereo tracking system is suggested and implemented. In the proposed system, face coordinates of a target person is detected from the sequential input stereo image pairs by using the YCbCr color model and phase-type correlation methods and then, using this data as well as the geometric information of the stereo tracking system, distance to the target from the stereo camera and 3-dimensional location information of a target person are extracted. Basing on these extracted data the pan/tilt system embedded in the stereo camera is controlled to adaptively track a moving person and as a result, moving trajectory of a target person can be obtained. From some experiments using 780 frames of the sequential stereo image pairs, it is analyzed that standard deviation of the position displacement of the target in the horizontal and vertical directions after tracking is kept to be very low value of 1.5, 0.42 for 780 frames on average, and error ratio between the measured and computed 3D coordinate values of the target is also kept to be very low value of 0.5% on average. These good experimental results suggest a possibility of implementation of a new stereo target tracking system having a high degree of accuracy and a very fast response time with this proposed algorithm.

• Journal of Information Display
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• 제6권4호
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• pp.26-34
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• 2005

In this paper, a new rectification scheme to transform the uncalibrated stereo image pair into the calibrated one is suggested and its performance is analyzed by applying this scheme to the reconstruction of the intermediate views for multi-view stereoscopic display. In the proposed method, feature points are extracted from the stereo image pair by detecting the comers and similarities between each pixel of the stereo image pair. These detected feature points, are then used to extract moving vectors between the stereo image pair and the epipolar line. Finally, the input stereo image pair is rectified by matching the extracted epipolar line between the stereo image pair in the horizontal direction. Based on some experiments done on the synthesis of the intermediate views by using the calibrated stereo image pairs through the proposed rectification algorithm and the uncalibrated ones for three kinds of stereo image pairs; 'Man', 'Face' and 'Car', it is found that PSNRs of the intermediate views reconstructed from the calibrated images improved by about 2.5${\sim}$3.26 dB than those of the uncalibrated ones.

• 디지털산업정보학회논문지
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• 제4권1호
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• pp.25-31
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• 2008

In this paper, we propose a new method that separates background and foreground from stereo images. This method can be improved automatic target tracking system by using disparity map of the stereo vision system and background-separating mask, which can be obtained camera configuration parameters. We use disparity map and camera configuration parameters to separate object from background. Disparity map is made with block matching algorithm from stereo images. A morphology filter is used to compensate disparity error that can be caused by occlusion area. We could obtain a separated object from background when the proposed method was applied to real stereo cameras system.

• 전자공학회논문지B
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• 제30B권6호
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• pp.59-66
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• 1993

Stereo vision is useful in obtaining three dimensional depth information from two images taken from different view points. Neural network modeling for stereo matching, the key step in stereo vision, is defined by an energy function satisfying with three constraints proposed by Marr and Poggio. Stereo matching is then carried out through the network to find minimum energy corresponding to the optimized solution of the problem. An algorithm for stereo matching using an analog neural network is presented here. The network can reduce errors in initial state an early iteration steps by adoption of continuous sigmoid function in stead of binary state. The experimental results show good matching performance for sparse random dot stereogram and real image.

• 전자공학회논문지B
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• 제31B권8호
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• pp.74-86
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• 1994

In this paper a hierarchical stereo matching algorithm to obtain the disparity in wavelet transformed domain by using locally adaptive window and weights is proposed. The pyramidal structure obtained by wavelet transform is used to solve the loss of information which the conventional Gaussian or Laplacian pyramid have. The wavelet transformed images are decomposed into the blurred image the horizontal edges the vertical edges and the diagonal edges. The similarity between each wavelet channel of left and right image determines the relative importance of each primitive and make the algorithm perform the area-based and feature-based matching adaptively. The wavelet transform can extract the features that have the dense resolution as well as can avoid the duplication or loss of information. Meanwhile the variable window that needs to obtain precise and stable estimation of correspondense is decided adaptively from the disparities estimated in coarse resolution and LL(low-low) channel of wavelet transformed stereo image. Also a new relaxation algorithm that can reduce the false match without the blurring of the disparity edge is proposed. The experimental results for various images show that the proposed algorithm has good perfpormance even if the images used in experiments have the unfavorable conditions.

• IEIE Transactions on Smart Processing and Computing
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• 제3권3호
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• pp.110-117
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• 2014

This paper reports a depth-adaptive sharpness adjustment algorithm for stereoscopic perception improvement, and presents its field-programmable gate array (FPGA) implementation results. The first step of the proposed algorithm was to estimate the depth information of an input stereo video on a block basis. Second, the objects in the input video were segmented according to their depths. Third, the sharpness of the foreground objects was enhanced and that of the background was maintained or weakened. This paper proposes a new sharpness enhancement algorithm to suppress visually annoying artifacts, such as jagging and halos. The simulation results show that the proposed algorithm can improve stereoscopic perception without intentional depth adjustments. In addition, the hardware architecture of the proposed algorithm was designed and implemented on a general-purpose FPGA board. Real-time processing for full high-definition stereo videos was accomplished using 30,278 look-up tables, 24,553 registers, and 1,794,297 bits of memory at an operating frequency of 200MHz.