本文選題：雙目立體媒體　切入點：深度計算　出處：《南京大學》2017年博士論文

【摘要】：VR、AR、IMAX3D等成為近年來人們耳熟能詳?shù)臒狳c詞匯,究其原因,主要是由于基于立體視覺媒體獲取設備的大量普及以及立體媒體數(shù)量的激增,讓更多人有機會了解、使用、研究立體媒體。盡管立體媒體的表達方式多樣,本文主要對其中模仿人眼方式記錄信息的雙目立體媒體,展開內(nèi)容分析和處理方面的研究。同傳統(tǒng)多媒體信息處理技術相比,立體媒體處理技術的關鍵在于對雙目視角之間區(qū)別和聯(lián)系關系的挖掘和利用。來自于平行視角之間的對立統(tǒng)一關系,既為內(nèi)容處理增加了更多線索,同時也增加了更多干擾,因而探索結合媒體新特性的新方法,才能切實提高立體媒體處理的質(zhì)量和效率。針對立體媒體內(nèi)容分析領域幾個關鍵性基礎問題,在總結國內(nèi)外研究現(xiàn)狀的基礎上,分析了存在的主要問題,并給出相應的解決方案。同時,對相關處理技術進行了深入探索。其中主要的創(chuàng)新點和貢獻包括如下幾個方面:1.提出了一種立體視頻深度快速估計方法,利用視頻幀間冗余信息,通過自適應運動插值,顯著提高計算效率,同時保證深度序列時域連續(xù)性�，F(xiàn)有立體媒體深度計算方法大多建立在雙目圖像立體匹配的基礎之上,此類方法通常需要設置合適的視差范圍,方能達到最佳計算效果,因而直接遷移到立體視頻上易造成深度序列不連續(xù)等現(xiàn)象。已有針對立體視頻的深度計算方法,為確保時域深度的連續(xù)性,需要引入大量全局優(yōu)化過程,因而計算效率很難得到保障。本文通過分析立體視頻特性,將細粒度深度計算和粗粒度深度估計通過運動矢量有機結合,提出了一種基于運動插值的深度快速估計方法。該方法不僅在精度上可以媲美全局優(yōu)化方法,在計算效率上更可以節(jié)省一半以上計算時間。2.提出了一種多對象似物性推薦方法,通過構建基于上下文感知的多對象似物性推薦模型,有效解決了逐幀似物性推薦所帶來的推薦不一致、計算冗余等問題�，F(xiàn)有似物性推薦研究多集中于圖像,而針對視頻的工作大多開始于圖像方法的逐幀使用,且主要面向運動物體或者顯著物體推薦。實驗表明,逐幀似物性推薦,不僅存在計算冗余,更重要的是其在時域上物體推薦結果易出現(xiàn)不一致性。為解決這些問題,本文提出了一種基于上下文感知的多對象似物性推薦方法,通過設置自適應映射策略,把空域似物性推薦和時域似物性推薦有機結合,為優(yōu)秀的似物性推薦研究成果應用于視頻中提供了通用且有效的解決方案。此外,針對目前缺少視頻多對象似物性推薦數(shù)據(jù)集的現(xiàn)狀,構建了一個平均物體數(shù)量達3.34的視頻多物體數(shù)據(jù)集,以推動本領域的相關研究。3.提出了一種基于視角融合的多顯著對象檢測方法,有效利用不同視角之間物體檢測的不一致性,進一步提升了顯著物體檢測的精度。目前顯著對象檢測主要基于場景中只有一個顯著對象的假設,有關多顯著對象檢測的問題,尚未形成規(guī)模性研究,并且已有和多顯著對象相關的工作也主要在單目圖像上開展。實驗表明,單目圖像多顯著對象檢測方法作用于雙目圖像時,易出現(xiàn)不同視角之間物體推薦不一致的現(xiàn)象。針對這一問題,本文提出了一種基于視角融合的多顯著對象檢測方法,通過探討平行視角間顯著物體框之間的關系,采用顯著性和似物性雙概率估計的策略,對顯著物體框的打分進行精化,從而提升最終多顯著物體檢測的準確性和精度。4.提出了一種平面動態(tài)立體感的展示方法,服務于廣泛存在的立體圖像,為實現(xiàn)立體圖像裸眼3D提供了新思路。如果沒有硬件輔助設備,存在于互聯(lián)網(wǎng)等處的立體圖像無法在普通顯示器上展示立體感的現(xiàn)象,是阻礙立體圖像進一步普及化的瓶頸。由于當前一些利用運動視差的平面3D動態(tài)展示方法缺乏對人眼感知立體的完整分析和建模,易造成展示結果存在閃爍、觀看不適等問題。本文通過對人眼視覺系統(tǒng)、運動視差、視覺暫留等現(xiàn)象的分析,提出了一種基于平面顯示設備的立體圖像動態(tài)展示方法,將立體圖像的3D感成功傳遞給用戶,為立體圖像的進一步發(fā)展創(chuàng)造了更多可能。5.提出了一種對立體視頻進行重對焦的方法,通過構建計算攝影模型,營造類單反拍攝的重對焦效果�，F(xiàn)有的立體視頻主要為電影院、VR/AR設備服務,很難在普通用戶生活中尋其蹤跡。事實上,利用立體視頻所隱含的深度信息,可以對視頻內(nèi)容實現(xiàn)更為豐富的內(nèi)容處理。僅依靠軟件方式實現(xiàn)視頻重對焦,其輸出結果很難擺脫人工處理痕跡。本文基于對攝影學中焦平面、景深、彌散圓等概念的理解,構建面向立體視頻重對焦的計算攝影模型,實現(xiàn)類單反效果的視頻重對焦,服務于普通用戶。在以上關鍵技術和內(nèi)容處理的基礎上,本文還給出了對未來一些研究方向的展望,展示了本文研究內(nèi)容的系統(tǒng)性和延展性,以及對相關研究領域的支撐作用,同時也說明本文研究成果在立體媒體研究領域具有良好的應用前景。
[Abstract]:VR, AR, IMAX3D has become a hot word in recent years the people the reason for having heard it many times, mainly due to a surge in the number of universal access to equipment based on stereo vision media and three-dimensional media, so that more people have the opportunity to learn, use, research on stereo media. Despite the expression of three-dimensional media diversity, this paper focuses on the binocular stereo media which mimics the recorded information of human way, carry out research content analysis and processing. Compared with the traditional multimedia information processing technology, three-dimensional media processing technology is the key to the mining of binocular visual angle between the difference and the relation between the unity of opposites. And from the perspective of the relationship between parallel, both for the content increased more clues, while also adding more interference, and to explore a new method of combining the new media features, in order to effectively improve the quality and efficiency of stereoscopic media processing Rate according to three-dimensional media content analysis field of several key basic problems, based on summarizing the domestic and foreign research status, analysis of the main problems, and gives the corresponding solutions. At the same time, in-depth exploration of the related processing technology. The main contributions are as follows: 1. put forward a fast stereo video depth estimation method, using the redundant information between the video frames, the motion adaptive interpolation, significantly improve the computational efficiency, at the same time to ensure the depth of time-domain sequence continuity. The existing stereo media depth calculation method based on the most in binocular stereo matching, this method usually need to set the appropriate to the disparity range. To achieve the best results, thus directly migrate to the stereo video easily caused by depth sequence discontinuous phenomena. According to the existing depth calculation of stereo video In order to ensure the continuity of the time domain method, the depth of the need to introduce a large number of global optimization process, so the computation efficiency is guaranteed. By analyzing the characteristics of stereo video, the fine-grained and coarse-grained depth calculation depth estimation by combining motion vector, proposed a motion interpolation based depth estimation method. This method is not only fast can the accuracy comparable to global optimization method, the computation efficiency can save more than half the computing time of.2. proposed a multi object analogues of recommendation method, by constructing multi object based on context awareness like material recommendation model can effectively solve the frame caused by the physical properties like recommended inconsistent calculation redundancy and other issues. The existing like material research focused on the recommendation for the video image, and most of the work started in the image frame and method of use, mainly for moving objects Or recommend significant objects. Experimental results show that the frame like properties recommended, not only exist redundant calculation, more important is the object in the time domain recommendation results prone to inconsistency. In order to solve these problems, this paper proposes a multi object based on context awareness like material recommendation method, by setting the adaptive mapping strategy the spatial properties, like the recommended and time domain analogs recommended combination, a general solution for the excellent and effective analogue recommendation research is applied to video. In addition, according to the present situation of the lack of video object like objects of recommended data sets, build a number of average objects up to 3.34 the video object data set, to promote research in the field of.3. presents a significant object detection method based on the fusion of the effective use of perspective, different perspectives between the object detection is not consistent, in Further enhance the saliency object detection accuracy. Currently significant object detection is mainly based on the scene only a significant object hypothesis, the more salient object detection problem, has not yet formed a large-scale study, and there are many and significant object related work mainly in monocular image. Experiments show that monocular image multiple salient objects detection method on the binocular image, prone to objects from different perspectives between recommended inconsistencies. Aiming at this problem, this paper proposes a multi object detection method was based on the perspective of integration through, to explore the relationship between the angle between parallel salient object frame, with significant and similar physical property estimation double probability strategy, refinement of the salient object frame rate, so as to enhance the accuracy and precision of the final.4. significant object detection presents a plane dynamic stereoscopic display 鏂規(guī)硶,鏈嶅姟浜庡箍娉涘瓨鍦ㄧ殑绔嬩綋鍥懼儚,涓哄疄鐜扮珛浣撳浘鍍忚８鐪，

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