本文選題：雙目視覺 + 立體匹配��； 參考：《天津大學(xué)》2016年碩士論文

【摘要】：視覺是人類獲取外界信息的主要途徑和方式,而研究如何模擬人類視覺并應(yīng)用到實(shí)際中能夠解決諸多難題,在醫(yī)療、航天、娛樂等領(lǐng)域均有著重要的意義。而計(jì)算機(jī)的迅猛發(fā)展,為視覺的模擬提供了有力的技術(shù)支撐,形成了一門熱門學(xué)科——計(jì)算機(jī)視覺。計(jì)算機(jī)視覺將計(jì)算機(jī)和攝像機(jī)有機(jī)的結(jié)合起來,通過攝像機(jī)對(duì)外界進(jìn)行成像并利用計(jì)算機(jī)對(duì)數(shù)字圖像進(jìn)行感知、識(shí)別和分析等,最終實(shí)現(xiàn)對(duì)現(xiàn)實(shí)場(chǎng)景空間的認(rèn)知理解。雙目立體視覺是計(jì)算機(jī)視覺中舉足輕重并充滿挑戰(zhàn)的課題之一,而立體匹配是其中的核心所在。立體匹配獲取的視差結(jié)果在很大程度上能夠反映三維空間中目標(biāo)的距離,這使得立體視覺能夠獲取平面視覺所不能提供的深度信息。因此立體匹配在立體視覺領(lǐng)域起到了至關(guān)重要的作用,對(duì)于立體匹配進(jìn)行深入研究探討具有極大的意義。另外,雖然研究者對(duì)立體匹配進(jìn)行了長(zhǎng)期的研究并提出了眾多立體匹配算法,也取得了不錯(cuò)的效果,但主要都是針對(duì)靜態(tài)圖像的,很少提出針對(duì)視頻序列的立體匹配算法。然而,對(duì)于動(dòng)態(tài)場(chǎng)景比如視頻序列而言,充分有效的利用視頻序列中獲得的動(dòng)態(tài)信息能夠很好的提升立體匹配的視差提取效果。因此本文基于立體匹配的重要性和針對(duì)視頻序列進(jìn)行立體匹配的不足,研究并提出了一種基于視頻序列的立體匹配算法。和現(xiàn)有方法相比,主要提出了一個(gè)新的計(jì)算模型,對(duì)自適應(yīng)權(quán)值部分進(jìn)行推導(dǎo)和建模,利用視頻序列中的光流信息來優(yōu)化權(quán)值的計(jì)算,提高其準(zhǔn)確度和精確度,最終提取準(zhǔn)確視差值。最后通過大量的實(shí)驗(yàn)對(duì)比和分析工作,驗(yàn)證了本文算法的有效性和可行性,取得了更理想的效果。
[Abstract]:Vision is the main way and way for human to obtain external information. Therefore, it is of great significance to study how to simulate human vision and apply it to solve many difficult problems in medical, aerospace, entertainment and other fields. The rapid development of computer provides powerful technical support for visual simulation and forms a hot subject-computer vision. The computer vision combines the computer and the camera organically, imaging the outside world by the camera and using the computer to perceive, recognize and analyze the digital image, and finally realizes the cognitive understanding of the real scene space. Binocular stereo vision is one of the most important and challenging topics in computer vision, and stereo matching is the core of it. The parallax results obtained by stereo matching can to a large extent reflect the distance of objects in three-dimensional space, which enables stereo vision to obtain depth information that plane vision cannot provide. Therefore, stereo matching plays an important role in stereo vision field, and it is of great significance for the further study of stereo matching. In addition, although many stereo matching algorithms have been studied and many stereo matching algorithms have been put forward for a long time, they are mainly aimed at static images, and few stereo matching algorithms are proposed for video sequences. However, for dynamic scenes such as video sequences, the full and effective use of the dynamic information obtained from the video sequences can improve the parallax extraction effect of stereo matching. Therefore, based on the importance of stereo matching and the deficiency of stereo matching for video sequences, a stereo matching algorithm based on video sequences is studied and proposed in this paper. Compared with the existing methods, a new computing model is proposed, which deduces and models the adaptive weight, and optimizes the weight calculation by using the optical flow information in the video sequence to improve its accuracy and accuracy. Finally, the accurate visual difference is extracted. Finally, the effectiveness and feasibility of the proposed algorithm are verified by a large number of experiments and analysis, and more ideal results are obtained.
【學(xué)位授予單位】：天津大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP391.41

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