Flash動(dòng)畫(huà)畫(huà)面的視覺(jué)特征與情感研究
[Abstract]:With the rapid development of multimedia and network technology, multimedia information has gradually become the main form of data transmitted on the Internet information high-speed network. Multimedia information includes image, audio and video information. Image is an important form of expression and contains rich emotional information. Flash animation is a popular multimedia form in recent years and widely used in education and teaching. It contains a large number of animated pictures, picture forms, various content, rich expression of emotion, the study of visual features and emotions of Flash animation picture has become the research topic of this paper. In this paper, the dynamic images in Flash animation are intercepted as the sample library of the study images, the parameters of the low-order visual features of each image are extracted, and 16 kinds of emotional adjectives (warm, cheerful, cheerful) are designed. ) describe the emotion of image expression, use 0-4 grade quantitative image in a certain emotion performance, 0 denote irrelevant, 4 denote full performance, completed the establishment of Flash animation image sample database. The emotion description and quantification of Flash animation images, and the extraction of the low order visual features of each Flash animation image, lay a foundation for the further research of image emotion classification and retrieval. The main work is as follows: (1) Establishment of Flash animation image sample library. Because we want to study the Flash animation picture, we need to establish an image sample database covering a large number of Flash animation pictures. Flash animation is usually divided into MTV, animation, advertisement, courseware, greeting card, etc. There are 6 kinds of games, such as MTV, animation, game, etc. The Flash animation is divided into 6 categories according to its expression content and form from the existing Flash animation library. Then according to the size of each kind of Flash animation information, we use Flash Decompiler Trillix software to intercept the image, such as the common MTV, reflects the large amount of information, the picture content is relatively rich, so the number of captured images is more. In view of the principle of each Flash animation to capture images, the sampling interval is as short as possible, the amount of image information is relatively abundant, and the repetition of similar images is avoided. A total of 2737 Flash animation images of 6 categories are intercepted to form the image sample library to be studied. (2) extracting the low order visual features of each image. The low-order visual features of the image include color, texture, shape and so on. The color of the Flash animation screen is obvious and often expresses emotion through the color rendering, so the extraction of the color feature is very important. At the same time, the texture features of the image are also studied and extracted. C and matlab are used to realize the color feature extraction of HSV color space. The color histogram feature vector 256-dimension is used as the color feature. At the same time, based on co-occurrence matrix texture feature extraction, energy, entropy, moment of inertia, energy, entropy and inertia moment are realized. The associated mean and standard deviation are used as the final eight parameters to represent the texture feature, and the low order visual feature table is made. (3) emotional description and quantification of Flash animation image. Each image contains and expresses different emotions, some of which are obvious and some are not. In order to describe the emotional performance of an image more comprehensively, 16 emotional adjectives are used, including warmth, tranquility, joy and vivacity. Funny, exaggerated, humorous, funny, desolate, boring, dreary, messy, illusory, thrilling, scary, intense, with 0-4 levels of quantitative images on the degree of an emotional adjective, 0 for nothing, 1 for slight performance, 2 for general performance, 3 for obvious performance, 4 for full performance. Through self-assessment and laboratory personnel to help complete the quantification of 2737 images, the main emotions expressed in each image were more accurate. Make image emotion analysis table.
【學(xué)位授予單位】:山東師范大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2012
【分類(lèi)號(hào)】:TP391.41
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