• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.9-16
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• 2002

This paper proposes a new 3D modeling technique using disparity-motion relationship and feature points. To generate the 3D model from real scene, generally, we need to compute depth of model vertices from the dense correspondence map over whole images. It takes much time and is also very difficult to get accurate depth. To improve such problems, in this paper, we only need to find the correspondence of some feature points to generate a 3D model of object without dense correspondence map. The proposed method consists of three parts, which are the extraction of object, the extraction of feature points, and the hierarchical 3D modeling using classified feature points. It has characteristics of low complexity and is effective to synthesize images with virtual view and to express the smoothness of Plain regions and the sharpness of edges.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.424-427
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• 2007

스테레오 영상으로부터 3차원 구조를 복원하기 위해서는 깊이맵에 해당하는 시차맵을 생성해야 한다. 시차맵 생성을 위해서는 정합비용을 계산하고, 집성한 후에 시차를 계산하는 절차로 이루어진다. 본 논문에서는 스테레오 영상으로부터 빠르고 안정된 시차맵을 생성하기 위해서 후처리 과정으로 각 스캔라인에 대해서 분산을 이용하여 세그멘테이션을 한 후에 세그멘테이션 별로 평균을 내어 객체간의 구분을 명확히 한다. 조밀 시차맵을 생성하기 위해서는 시차 계산에 실패한 화소들에 대해서도 시차를 계산해야 하는데 본 논문에서는 간단하게 인접 화소의 값을 복사하는 방법으로 홀을 메우는 방법을 제안한다. 실제 환경에서의 다양한 스테레오 영상에 대한 실험 결과들은 제안된 시차맵 생성과 홀을 메우는 방법이 기존의 시차맵 생성 기법만큼 빠르고 기존의 방법보다 좀더 안정적이고 다양한 컴퓨터 비전 시스템응용에 적용될 수 있음을 보여준다.

• Journal of KIISE
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• v.44 no.9
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• pp.932-945
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• 2017

In this paper, a new hardware and software architecture for a stereo vision processing system including rectification, disparity estimation, and visualization was developed. The developed method, named LArge scale stereo matching method using Support Point Interpolation (LASPI), shows excellence in real-time processing for obtaining dense disparity maps from high quality image regions that contain high density support points. In the real-time processing of high definition (HD) images, LASPI does not degrade the quality level of disparity maps compared to existing stereo-matching methods such as Efficient LArge-scale Stereo matching (ELAS). LASPI has been designed to meet a high frame-rate, accurate distance resolution performance, and a low resource usage even in a limited resource environment. These characteristics enable LASPI to be deployed to safety-critical applications such as an obstacle recognition system and distance detection system for autonomous vehicles. A Field Programmable Gate Array (FPGA) for the LASPI algorithm has been implemented in order to support parallel processing and 4-stage pipelining. From various experiments, it was verified that the developed FPGA system (Xilinx Virtex-7 FPGA, 148.5MHz Clock) is capable of processing 30 HD ($1280{\times}720pixels$) frames per second in real-time while it generates disparity maps that are applicable to real vehicles.