EAGER: Aesthetically Empowering Novice Photographers

EAGER：赋予新手摄影师审美力量

• 批准号: 1048599
• 负责人: Brian Barsky
• 金额: $ 9.85万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1048599&HistoricalAwards=false
• 关键词: EAGER; Aesthetically; Empowering; Novice; Photographers

Digital photography and the Internet are enabling ordinary people to take and save photographs at negligible variable cost. As a result amateurs often accumulate large volumes of images. They are then confronted with the tedious chore of sorting through their massive collections to select the most aesthetically pleasing pictures. The onerous nature of this task is exacerbated by the sense of many people that articulating and quantifying aesthetic attributes is esoteric. Automated evaluation of photographs based on user-defined criteria is in a nascent stage, lacking the flexibility to provide a personalized experience tailored to the individual user. Current systems develop a set of classifiers based on an image dataset, but this approach impedes adaptation to user preferences and inhibits the flexibility needed to develop new heuristics for aesthetics. In this exploratory project the PI aims to raise the overall aesthetic quality of amateur photography by creating software to automatically sort and filter a collection of images using a set of analytically-constructed aesthetic principles, in a manner analogous to what is done by a professional photographer. The approach is based upon the concept of a hierarchal modular classifier that can be customized for different individuals, so that each user can have a classifier that characterizes his or her preferences. Since the classifier is a simple arrangement of modules, one can imagine that even a single user could design multiple classifiers that cater to his or her every preference; for example, the user could have a classifier to help select the best landscape photographs s/he has taken, and another to select the best portraits. Broader Impacts: Comparison of data taken from different demographics will enhance our understanding of how cultural, social, or other background factors influence individual preferences in aesthetics. The ability to tune image searches so as to return images that are more aesthetically pleasing according to specific criteria will have commercial implications (e.g., when companies endeavor to create designs, products, or services that are tailored to different audiences). The work has social networking applications as well, since the algorithms developed could enable people to find others with similar preferences. The PI's system will teach amateur photographers how to improve their picture-taking skills, by showing them specific possible modifications that could be applied to enhance their photographs. Project outcomes will lay the foundation for technology that can automatically post-process images so as to improve their aesthetic quality. Thus, this research ultimately will improve the overall quality of the images that are available on the Web.

数码摄影和互联网使普通人能够以微乎其微的可变成本拍摄和保存照片。 因此，业余爱好者经常积累大量图像。 然后，他们面临着对大量收藏进行分类以选择最美观的图片的繁琐工作。 许多人认为阐明和量化美学属性是深奥的，这加剧了这项任务的繁重性。 基于用户定义标准的照片自动评估还处于起步阶段，缺乏为个人用户提供个性化体验的灵活性。 当前的系统开发了一组基于图像数据集的分类器，但这种方法阻碍了对用户偏好的适应，并抑制了开发新的美学启发式方法所需的灵活性。 在这个探索性项目中，PI 的目标是通过创建软件，使用一组分析构建的美学原理自动排序和过滤图像集合，以类似于专业摄影师所做的方式来提高业余摄影的整体审美质量。 该方法基于可以为不同个人定制的分层模块化分类器的概念，以便每个用户都可以拥有一个表征他或她的偏好的分类器。 由于分类器是模块的简单排列，因此可以想象，即使是单个用户也可以设计多个分类器来满足他或她的每一个偏好；例如，用户可以使用一个分类器来帮助选择他/她拍摄的最佳风景照片，并使用另一个分类器来选择最佳的肖像照片。 更广泛的影响：比较不同人口统计数据将增强我们对文化、社会或其他背景因素如何影响个人审美偏好的理解。 调整图像搜索以便根据特定标准返回更美观的图像的能力将具有商业意义（例如，当公司努力创建适合不同受众的设计、产品或服务时）。 这项工作也有社交网络应用，因为开发的算法可以让人们找到具有相似偏好的其他人。 PI 的系统将教业余摄影师如何提高他们的拍照技巧，向他们展示可用于增强照片效果的具体可能修改。 项目成果将为自动对图像进行后处理以提高其审美质量的技术奠定基础。 因此，这项研究最终将提高网络上可用图像的整体质量。