本文選題：照片 + 計算機美學(xué)��； 參考：《云南大學(xué)》2014年碩士論文

【摘要】：近幾年來,隨著家用相機的普及和手機自帶拍照功能的逐漸增強,并且在許多社交網(wǎng)站和手機應(yīng)用中都加入了照片分享功能,因此讓更多的人喜歡上了攝影,從而導(dǎo)致現(xiàn)今照片的數(shù)量呈爆炸式增長。因此,利用先進的計算機技術(shù)來幫助人類,在基于計算機美學(xué)的相關(guān)技術(shù)之上,對各類照片進行美感評價與分析這一研究領(lǐng)域越來越受到各方學(xué)者的關(guān)注。傳統(tǒng)的對照片美感品質(zhì)評價僅是依靠攝影師或者觀賞者們基于自身對美學(xué)和攝影理論的理解來做出主觀的評判,而計算機美學(xué)的出現(xiàn)與興起正是對原有照片美感品質(zhì)評價的主觀性和單一性做了進一步的完善。此外,通過計算機進行照片特征值的提取及機器學(xué)習(xí)和分類的過程,模擬人腦對照片美感品質(zhì)的評判,建立了美學(xué)和人工智能及模式識別之間的橋梁。因此,該項研究屬于攝影學(xué)、美學(xué)和計算機科學(xué)等多個學(xué)科相互交叉與融合的創(chuàng)新性前沿研究課題,且具有相當(dāng)重要的理論研究價值以及廣闊的應(yīng)用前景。 本論文在圖形圖像處理技術(shù)、攝影理論和計算機美學(xué)的背景支撐下,有效結(jié)合照片中的各種特征,共提出了三十八種能較好表征各類照片不同特點的數(shù)字化特征。實驗中所用到的照片包括人像、動物、植物、靜物、建筑、風(fēng)景和夜景共七個類別。在對這些照片進行美感品質(zhì)客觀評價時,依據(jù)機器學(xué)習(xí)理論的指導(dǎo),本文使用了支持向量機(SVM)、Adaboost、線性回歸分類和隨機森林這四種分類器,并且在進行分類實驗時使用了十交叉檢驗的方法。在對實驗結(jié)果的分析中發(fā)現(xiàn),不同特征對不同類別照片美感品質(zhì)的影響存在著一定的相似性,但同時也有顯著的差異,如結(jié)構(gòu)特征對人像照片美感品質(zhì)的影響程度相比景物類照片更高。本文的主要內(nèi)容有如下幾個方面： 首先,對計算機美學(xué)和攝影基礎(chǔ)理論進行簡要的介紹與概述,并將照片美感品質(zhì)的主觀判斷依據(jù)和攝影基本理論以及計算機美學(xué)三者之間的關(guān)系進行充分的分析。 其次,以照片美感品質(zhì)的主觀判斷依據(jù)和攝影基本理論為基礎(chǔ),分別提出了照片的布局與結(jié)構(gòu)、照片的亮度和照片的暗通道等多種能夠較好表征照片美感品質(zhì)的數(shù)字特征,并通過實驗分析不同特征在對照片美感客觀評價時的影響程度。 最后,依據(jù)照片的類別在所提特征中選取相應(yīng)特征,對各類照片美感品質(zhì)在多種分類器中進行客觀分類實驗及結(jié)果分析,從而對照片美感做出客觀評價。 實驗表明,使用本文所提的三十八種數(shù)字特征對各類照片進行客觀的美感品質(zhì)評價是行之有效的,該項研究不僅為照片的美感品質(zhì)分析與評價提供了一種全新的方法,還能幫助攝影師從自己的拍攝作品中選取出其中具有較高美感品質(zhì)的這些照片,或者在照片拍攝之后馬上能顯示其高/低美感品質(zhì)從而來輔助拍攝者決定將這張照片保存或是重拍等廣泛的用途。
[Abstract]:In recent years, with the popularity of home cameras and the gradual increase in the ability to take photos with mobile phones, photo sharing has been added to many social networking sites and mobile apps, so that more people are interested in photography. This has led to an explosive increase in the number of photographs today. Therefore, using advanced computer technology to help human, on the basis of computer aesthetics related technology, the aesthetic evaluation and analysis of all kinds of photographs has been paid more and more attention by scholars from all over the world. The traditional evaluation of the aesthetic quality of photographs is based on the understanding of aesthetics and photography theory by photographers or viewers. The appearance and rise of computer aesthetics have further improved the subjectivity and singularity of the original photo aesthetic quality evaluation. In addition, the process of feature extraction, machine learning and classification by computer is used to simulate the evaluation of the aesthetic quality of photographs by human brain, and a bridge between aesthetics, artificial intelligence and pattern recognition is established. Therefore, this research belongs to the innovative frontier research subject, such as photography, aesthetics, computer science and so on, which intersects and merges each other, and has quite important theoretical research value and broad application prospect. Based on the background of graphics and image processing, photography theory and computer aesthetics, this paper presents 38 digital features which can better represent the different characteristics of various kinds of photographs. The photos used in the experiment included human figures, animals, plants, still life, architecture, scenery and night scenes. Based on the guidance of machine learning theory, four classifiers, support vector machine (SVM), linear regression classification and random forest classification, are used to evaluate the aesthetic quality of these photos. And the method of ten cross-test is used in the classification experiment. In the analysis of the experimental results, it is found that the influence of different characteristics on the aesthetic quality of different types of photos has some similarities, but there are also significant differences. For example, the influence of structural features on the aesthetic quality of portrait photos is higher than that of landscape photographs. The main contents of this paper are as follows: First of all, the basic theories of computer aesthetics and photography are briefly introduced and summarized, and the relationship between the subjective judgment of the aesthetic quality of photographs, the basic theory of photography and the computer aesthetics is fully analyzed. Secondly, based on the subjective judgment of the aesthetic quality of photographs and the basic theory of photography, this paper puts forward the digital features which can better characterize the aesthetic quality of photographs, such as the layout and structure of photographs, the brightness of photographs and the dark channels of photographs. The influence of different characteristics on the objective evaluation of the aesthetic perception of photographs is analyzed through experiments. Finally, according to the category of photos in the proposed features selected the corresponding features, the aesthetic quality of all kinds of photos in a variety of classifiers for objective classification experiments and results analysis, so as to make an objective evaluation of the aesthetic perception of photos. The experiment shows that it is effective to use the 38 digital features mentioned in this paper to evaluate the aesthetic quality of all kinds of photos. This study not only provides a new method for the analysis and evaluation of the aesthetic quality of photographs. It can also help photographers to pick out these pictures that have a higher aesthetic quality from their own photographs. Or it can show its high / low aesthetic quality immediately after the photo is taken to assist the photographer in deciding to save or remake the photo for a wide range of purposes.
【學(xué)位授予單位】：云南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TB85;TP391.41

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相關(guān)期刊論文 前1條

1 王偉凝;蟻靜緘;賀前華;;可計算圖像美學(xué)研究進展[J];中國圖象圖形學(xué)報;2012年08期

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本文編號：1974646