面向敦煌壁画的移动视觉搜索模型研究

[目的/意义]保护敦煌文化遗产,为敦煌壁画提供移动视觉搜索服务,以助用户高效、便捷地获取敦煌壁画丰富知识资源。[方法/过程]构建基于BoW的图像底层特征匹配和基于主题标签的高层语义关联的移动视觉搜索模型,用SIFT提取图像局部特征,K-means生成有K个视觉单词组成的视觉词典,计算图像映射到视觉词典的TF-IDF向量,通过内积计算相似度匹配图像并排序;根据图像主题添加语义标签,提取最匹配图像的标签实现语义关联搜索;最后收集1200张敦煌壁画图片验证模型的有效性。[结果/结论]在视觉单词数为1000时BoW+SIFT的图像搜索耗时163ms,且图像大小在0.5-2.5倍范围的准确率在83.7%以上,可有效搜索主题语义关联图像。     

渝东南地区乡镇初级中学学生思想品德现状调查

通过对渝东南九县一市一区乡镇初级中学学生思想品德现状的分层随机抽样调查，得出了“目前乡镇初级中学学生的思想品德状况令人堪忧”的结论，并探讨了导致这一状况的成因，提出了有针对性的教育建议。     

Ancient Mural Classification Method Based on Improved AlexNet Network

ABSTRACT

As an important part of art and culture, ancient murals depict a variety of different artistic images, and these individual images have important research value. For research purposes, it is often important to first determine the type of objects represented in a painting. However, the mural painting environment makes datasets difficult to collect, and long-term exposure leads to underlying features that are not distinct, which makes this task challenging. This study proposes a convolutional neural network model based on the classic AlexNet network model and combines it with feature fusion to automatically classify ancient mural images. Due to the lack of large-scale mural datasets, the model first expands the dataset by applying image enhancement algorithms such as scaling, brightness conversion, noise addition, and flipping; then, it extracts the underlying features (such as fresco edges) shared by the first stage of a dual channel structure. Subsequently, a second-stage deep abstraction is conducted on the features extracted by the first stage using a two-channel network, each of which has a different structure. The obtained characteristics from both channels are merged, and a loss function is constructed to obtain the classification result. This approach improves the model's robustness and feature expression ability. The model achieves an accuracy of 84.24%, a recall rate of 84.15%, and an F1-measure of 84.13% when applied to a constructed mural image dataset. Compared with the AlexNet model and other improved convolutional neural network models, the proposed model improves each evaluation index by approximately 5%, verifying the rationality and effectiveness of the model for automatic mural image classification. The mural classification model proposed in this paper comprehensively considers the influences of network width and depth and can extract rich details from mural images from multiple local channels. An effective classification method could help researchers manage and protect mural images in an orderly fashion and quickly and effectively search for target images in a digital mural library based on a specified image category, aiding mural condition monitoring and restoration efforts as well as archaeological and art historical research.     

浅析学院宏观调控与教学部自立管理相结合的新体制

介绍了海大培训学院教学管理的组织框架——学院宏观调控与教学部自立管理相结合的新模式。     

谈壁画艺术的审美与功能

壁画是依托建筑墙面而存在的公共艺术。从属于建筑的功能和设计风格进行装饰是壁画的主要特点，满足公众的审美需求是壁画创作的基本原则。人类文明程度的普遍提高和现代建筑设计理念的发展，增强了大众对审美时尚的需求和变化，壁画艺术家在追求现代建筑精神与人文精神的完美结合中，以传统和现代工艺材料为造型手段，在承袭传统壁画艺术精髓和各民族优秀造型艺术特点的基础上，创造出审美内涵更加丰富、功能更加多元的现代壁画艺术。     

改革创新,不断完善和发展高自考助学的教育体系

文章以海淀走读大学培训中心为例 ,介绍了高教自考助学体系的三个组成部分 :主体部分、配套部分和探索部分     

墓葬壁画研究的方法论探讨——从美术考古的角度出发

要加强对墓葬壁画研究的系统性和深入性,有必要从一个学科的高度,对墓葬壁画的研究进行一些方法论规定性的思索。对某一时期墓葬壁画的研究大体可分为这样几个步骤或层次：一、利用传统考古学的地层学和类型学的方法对壁画墓资料进行系统的整理;二、结合文献史料,对墓葬壁画的文化背景、源流及艺术风格等问题的探讨;三、对壁画功能和意义进行解读,从而复原图像与墓葬本身的关系,以及图像与丧葬意识和行为过程的关系;四、将对墓葬壁画的研究扩展到整个文化史范围,努力达到复原古代社会文化的目的。     

原始艺术的发生与特点

原始社会的生活是原始艺术萌生与发展的土壤。原始诗歌伴随劳动产生，其最初阶段，劳动、音乐、诗歌互相紧密联系，三位一体。原始人类以石头、陶器、骨牙器等为物质依托，创造并发展了绘画和雕塑艺术。原始艺术的发生和初期发展，又与原始宗教、原始巫术关系密切。在原始人的宗教信仰中，图腾信仰带有普遍性，其对原始艺术的影响亦带普遍性。原始神话把远古人类的图腾信仰表现出来，带有行为和道德规范化意义。原始的。ｃ理冲动导致原始歌舞的发生。原始先民的“自意识”发展成熟起来，原始艺术便从单纯的自娱性质进入到既自娱又娱人的性质。     

市场经济下的中国当代壁画

针对目前壁画发展与市场结合的过程中出现的一些问题,从分析中国当代壁画的发展现状入手,选取了目前存在的一些热点问题和现象,提出了壁画家如何面对市场的建议,最后,运用社会主义市场经济理论对中国当代壁画生存与发展作了初步的结论。     

浅谈装饰艺术的影像

本文阐述了影像对装饰造型的意义,分析了影像在几种有代表性的艺术形式中的体现,及其对装饰造型设计的启示。