三維室內(nèi)場(chǎng)景分析及合成算法研究
[Abstract]:In the fields of computer graphics and computer vision, modeling of various 3D scenes has been a hot topic and a valuable research topic for scholars at home and abroad. With the rapid development of science and technology, such as computer simulation and virtual reality, 3D modeling of indoor scene is more widely used in fire rescue, hostage rescue, secret room escape and archaeological excavation. Indoor scene modeling is of great significance. At present, there are three methods for modeling objects or scenes: modeling with 3D software, collecting information through instruments and devices, modeling by image or video, modeling at time cost by these methods. The operational complexity and modeling effect are more or less inadequate, so the automatic synthesis of 3D indoor scene has become a challenging problem in the field of scene modeling in recent years. In this paper, the geometric relationship of objects and the position distribution of objects in the scene are analyzed, and on this basis, the automatic synthesis method of 3D indoor scene is realized. The main contributions of this paper are as follows: (1) this paper realizes the algorithms of detecting and extracting the intersection, proximity and support of three kinds of spatial relations between objects in the scene, and at the same time realizes the extraction of the support plane in the scene. The symbiotic relationship of object support is constructed. The geometric analysis of the scene provides a theoretical basis for optimizing the scene composition algorithm. (2) in this paper, the GMM is used to fit the position of the object on the support surface, and the location distribution model is obtained. Firstly, a file is established to store the statistical objects in the normalized position on the support surface. The number of coordinates represents the number of times the objects appear in the scene library. Then the Gao Si hybrid model is used to fit the contents of the file and the location distribution model is obtained. (3) in this paper, an automatic synthesis method of 3D indoor scene is proposed. The initial indoor scene and the description of small objects to be added to the scene are given by the user. With the help of the material library to select small objects, the scene composition algorithm is used to realize the automatic placement of these small objects, which shows the rich evolution process of simple scenes. This method not only reflects the design requirements of users, but also avoids tedious manual operation.
【學(xué)位授予單位】:北京交通大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2016
【分類(lèi)號(hào)】:TP391.41
【相似文獻(xiàn)】
相關(guān)期刊論文 前10條
1 伍立華,鄒北驥,彭永進(jìn);一種基于塊體變形的人臉合成算法[J];計(jì)算機(jī)工程與應(yīng)用;2001年15期
2 呂巖,唐廣志,盧奕南;數(shù)據(jù)合成算法在醫(yī)療診斷中的應(yīng)用[J];試驗(yàn)技術(shù)與試驗(yàn)機(jī);2005年03期
3 李紅梅;丁振國(guó);周水生;周利華;;一種改進(jìn)的元搜索排序合成算法[J];華南理工大學(xué)學(xué)報(bào)(自然科學(xué)版);2008年09期
4 陳衛(wèi)衛(wèi);王艷;;無(wú)回溯反向鏈合成算法的研究與改進(jìn)[J];中國(guó)科技信息;2010年17期
5 林茂六;舒冬梅;高曉明;;小數(shù)頻率信號(hào)的合成算法及其數(shù)字頻譜分析[J];電子測(cè)量與儀器學(xué)報(bào);1993年04期
6 張昭理;洪帆;;一個(gè)基于有色Petri網(wǎng)的自動(dòng)Web服務(wù)合成模型[J];計(jì)算機(jī)科學(xué);2008年06期
7 李小平,徐曉飛;非同起點(diǎn)加工的多機(jī)調(diào)度合成算法[J];計(jì)算機(jī)學(xué)報(bào);2002年08期
8 張大陸;王炫召;;一種半自動(dòng)化Web服務(wù)合成的算法[J];計(jì)算機(jī)科學(xué);2007年02期
9 張素,楊申,徐乃平,戴冠中;一種任意形狀圖象的多分辨合成算法研究[J];計(jì)算機(jī)應(yīng)用研究;1999年06期
10 竇萬(wàn)峰;異步協(xié)同設(shè)計(jì)中的對(duì)象版本合成[J];機(jī)械設(shè)計(jì);2004年01期
相關(guān)會(huì)議論文 前4條
1 周樹(shù)蕙;范晨輝;顧寧;宗宇偉;丁志剛;張紹華;;QoS驅(qū)動(dòng)的Web Services方案相關(guān)合成[A];第二十三屆中國(guó)數(shù)據(jù)庫(kù)學(xué)術(shù)會(huì)議論文集(研究報(bào)告篇)[C];2006年
2 馮平;張治中;;WAP業(yè)務(wù)監(jiān)測(cè)技術(shù)的研究與實(shí)現(xiàn)[A];2009年全國(guó)無(wú)線電應(yīng)用與管理學(xué)術(shù)會(huì)議論文集[C];2009年
3 劉祥凱;彭強(qiáng);夏旭;;改進(jìn)的基于深度圖的視點(diǎn)合成算法[A];第18屆全國(guó)多媒體學(xué)術(shù)會(huì)議(NCMT2009)、第5屆全國(guó)人機(jī)交互學(xué)術(shù)會(huì)議(CHCI2009)、第5屆全國(guó)普適計(jì)算學(xué)術(shù)會(huì)議(PCC2009)論文集[C];2009年
4 薛峰;張佑生;江巨浪;胡敏;;基于自組織特征映射的紋理合成[A];幾何設(shè)計(jì)與計(jì)算的新進(jìn)展[C];2005年
相關(guān)碩士學(xué)位論文 前10條
1 楊佳麗;三維室內(nèi)場(chǎng)景分析及合成算法研究[D];北京交通大學(xué);2016年
2 朱榮花;多假設(shè)航跡合成算法的研究[D];哈爾濱工業(yè)大學(xué);2007年
3 雅孺;運(yùn)動(dòng)合成算法的研究與實(shí)現(xiàn)[D];上海交通大學(xué);2011年
4 周樹(shù)蕙;QoS驅(qū)動(dòng)的Web Services合成方法研究[D];復(fù)旦大學(xué);2008年
5 王炫召;Web Services合成中若干關(guān)鍵問(wèn)題的研究[D];同濟(jì)大學(xué);2006年
6 蔣文娟;新視角合成方法研究[D];上海交通大學(xué);2009年
7 潘剛;基于多分辨率小波紋理合成算法及其應(yīng)用[D];天津大學(xué);2008年
8 林u!;多視點(diǎn)自由立體圖像合成算法研究[D];天津大學(xué);2007年
9 于健;基于多通道相控陣線圈的磁共振圖像合成算法研究[D];東北大學(xué);2011年
10 熊莉;多傳感器多目標(biāo)航跡合成算法研究[D];哈爾濱工業(yè)大學(xué);2007年
,本文編號(hào):2135405
本文鏈接:http://sikaile.net/kejilunwen/ruanjiangongchenglunwen/2135405.html