本文選題：照片 + 計(jì)算機(jī)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(jī)的普及和手機(jī)自帶拍照功能的逐漸增強(qiáng),并且在許多社交網(wǎng)站和手機(jī)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(jìn)的計(jì)算機(jī)技術(shù)來幫助人類,在基于計(jì)算機(jī)美學(xué)的相關(guān)技術(shù)之上,對各類照片進(jìn)行美感評價(jià)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(jià)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(jì)算機(jī)美學(xué)的出現(xiàn)與興起正是對原有照片美感品質(zhì)評價(jià)的主觀性和單一性做了進(jìn)一步的完善。此外,通過計(jì)算機(jī)進(jìn)行照片特征值的提取及機(jī)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(xiàng)研究屬于攝影學(xué)、美學(xué)和計(jì)算機(jī)科學(xué)等多個(gè)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(jià)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(jì)算機(jī)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(diǎn)的數(shù)字化特征。實(shí)驗(yàn)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(gè)類別。在對這些照片進(jìn)行美感品質(zhì)客觀評價(jià)時(shí),依據(jù)機(jī)器學(xué)習(xí)理論的指導(dǎo),本文使用了支持向量機(jī)(SVM)、Adaboost、線性回歸分類和隨機(jī)森林這四種分類器,并且在進(jìn)行分類實(shí)驗(yàn)時(shí)使用了十交叉檢驗(yàn)的方法。在對實(shí)驗(yàn)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(shí)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(gè)方面： 首先,對計(jì)算機(jī)美學(xué)和攝影基礎(chǔ)理論進(jìn)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(jì)算機(jī)美學(xué)三者之間的關(guān)系進(jìn)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(shí)驗(yàn)分析不同特征在對照片美感客觀評價(jià)時(shí)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(jìn)行客觀分類實(shí)驗(yàn)及結(jié)果分析,從而對照片美感做出客觀評價(jià)。 實(shí)驗(yàn)表明,使用本文所提的三十八種數(shù)字特征對各類照片進(jìn)行客觀的美感品質(zhì)評價(jià)是行之有效的,該項(xiàng)研究不僅為照片的美感品質(zhì)分析與評價(jià)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

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

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

，

本文編號：1974646