学术动态
学术动态
博士李晶出国参加国际会议回国报告

1、汇报安排
汇报题目:参加 SPIE Optical Engineering + Applications, part of the SPIE Optics + Photonics 2017 event 参会报告
汇报时间:2017年9月8日(星期五)9: 00
汇报地点:机械工程学院激光所会议室(西二东118)
汇报人:李晶
 
2、参加国际会议信息
会议名称:SPIE Optical Engineering + Applications
会议时间:6-10 August 2017
会议地点:Convention Center Exhibit Hall 2, San Diego, California, USA
会议简介:SPIE Optical Engineering + Applications, the premier conference for the latest developments in optical design and engineering, including photonic devices and applications, x-ray, gamma-ray, and particle technologies, image and signal processing, astronomical optics and instrumentation, remote sensing, and space optical systems. Conferences are grouped into program tracks based on related technology topics. Each conference is then organized into sessions of related papers. SPIE conference papers are published in the Proceedings of SPIE and available via the SPIE Digital Library, the world’s largest collection of optics and photonics research.
会议交流工作:
Poster presentation: Global stereo matching algorithm based on disparity range estimation
报告人:李晶
 
3、参会论文信息
Title: Global stereo matching algorithm based on disparity range estimation
Author: Jing Li, Hong Zhao* and Feifei Gu
Abstract: The global stereo matching algorithms are of high accuracy for the estimation of disparity map, but the time-consuming in the optimization process still faces a curse, especially for the image pairs with high resolution and large baseline setting. To improve the computational efficiency of the global algorithms, a disparity range estimation scheme for the global stereo matching is proposed to estimate the disparity map of rectified stereo images in this paper. The projective geometry in a parallel binocular stereo vision is investigated to reveal a relationship between two disparities at each pixel in the rectified stereo images with different baselines, which can be used to quickly obtain a predicted disparity map in a long baseline setting estimated by that in the small one. Then, the drastically reduced disparity ranges at each pixel under a long baseline setting can be determined by the predicted disparity map. Furthermore, the disparity range estimation scheme is introduced into the graph cuts with expansion moves to estimate the precise disparity map, which can greatly save the cost of computing without loss of accuracy in the stereo matching, especially for the dense global stereo matching, compared to the traditional algorithm. Experimental results with the Middlebury stereo datasets are presented to demonstrate the validity and efficiency of the proposed algorithm.
 
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