【摘要】：隨著計(jì)算機(jī)圖形學(xué)和計(jì)算機(jī)視覺的快速發(fā)展,高級(jí)圖像編輯技術(shù)近些年來(lái)發(fā)展非常迅速,越來(lái)越多的研究開始關(guān)注對(duì)圖像內(nèi)容的理解,如圖像模型的材質(zhì)和表面結(jié)構(gòu)信息。本文提供了一種便捷高效的僅通過(guò)簡(jiǎn)單的用戶交互從單張照片中獲得材質(zhì)以及外觀模型的方法。對(duì)于一張?jiān)谌我猸h(huán)境光照下的近平面材質(zhì)圖片,我們僅需要少量的用戶交互對(duì)局部信息進(jìn)行約束,就可獲得模型的材質(zhì)信息(包括漫反射率,鏡面反射率,粗糙度),圖片上各個(gè)像素的法向量信息。并且可以將計(jì)算獲得的材質(zhì)模型在任意給定光源下渲染。算法主要分四步:首先將輸入圖片上的高光和陰影部分移除,并用相似的片段補(bǔ)全從而將圖片轉(zhuǎn)變?yōu)槁瓷鋱D片;然后將獲得的圖片通過(guò)本征分解,分解為反射率圖和陰影圖,由于基礎(chǔ)的分解算法固有的不適定性問(wèn)題,難以處理具有復(fù)雜反射率變化和陰影變化的局部細(xì)節(jié),本文在這些區(qū)域通過(guò)用戶用畫筆添加約束將耦合的兩種信息區(qū)分出來(lái);其次以陰影圖片為輸入,采用聯(lián)合優(yōu)化的方式同時(shí)優(yōu)化法向量信息和光照信息;最后通過(guò)反射率圖像以及用戶提供的材質(zhì)信息,對(duì)全圖的各個(gè)像素進(jìn)行材質(zhì)建模。于此同時(shí),我們提供了一個(gè)便捷的圖形界面供用戶使用,可以使用戶的交互更易操作,并且可以實(shí)時(shí)查看處理的中間結(jié)果,并針對(duì)圖片本身的特點(diǎn)對(duì)結(jié)果進(jìn)行優(yōu)化。實(shí)驗(yàn)結(jié)果顯示我們的算法在處理復(fù)雜光照下的圖片時(shí),無(wú)論是在幾何建模還是材質(zhì)建模過(guò)程中,都可以保留較為細(xì)致的細(xì)節(jié)結(jié)果。
[Abstract]:With the rapid development of computer graphics and computer vision, advanced image editing technology has developed very rapidly in recent years. More and more research has begun to focus on the understanding of image content, such as image model material and surface structure information. This paper provides a convenient and efficient way to obtain material and appearance models from a single photo only through simple user interaction. For a picture of near-plane material under arbitrary illumination, we can obtain the material information of the model (including diffuse reflectivity, mirror reflectivity) by using only a small amount of user interaction to constrain the local information. Roughness), the normal vector information for each pixel on the picture. And the calculated material model can be rendered under any given light source. The algorithm is mainly divided into four steps: first, removing the highlights and shadows on the input images, and then converting the images into diffuse reflection images by using similar fragments, and then decomposing the obtained images into reflectivity maps and shadow images through intrinsic decomposition. Due to the inherent ill-posed problem of the basic decomposition algorithm, it is difficult to deal with the local details with complex reflectivity change and shadow variation. In this paper, two kinds of coupled information are distinguished in these areas by adding constraints with brush. Secondly, the shaded image is used as input, and the normal vector information and illumination information are optimized simultaneously by the way of joint optimization. Finally, through the reflectivity image and the material information provided by the user, the material modeling of each pixel of the whole image is carried out. At the same time, we provide a convenient graphical interface for users to use, which can make the user's interaction easier to operate, and can view the intermediate results in real time, and optimize the results according to the characteristics of the picture itself. The experimental results show that our algorithm can retain more detailed results in the process of geometric modeling and material modeling when dealing with images under complex illumination.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41

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