A revolutionary project for film and media studies scholars developed by faculty and staff at Bowdoin is making global waves in the academic world, buoyed in part by the ongoing pandemic.
“Kinolab” is a living, online, searchable repository for narrative movie and series clips “and a great tool for teaching,”says Assistant Professor of Romance Languages and Literatures and Cinema StudiesAllison Cooper。“Since we launched an updated platform in July 2020, there has been a nearly 400 percent increase in traffic.” “I have always been interested in how the digital revolution allows us to rethink film as a medium, but a special opportunity presented itself when I was researching a book on cinematic representations of the city of Rome.”
This realization instilled a desire in Cooper. “I envisioned a database that would allow us to find all the examples of, say, the long take in the works of Antonioni or the tracking shot in the movies of Fellini, and so on. I couldn't believe there was no way to do that and so I realized I had to invent the way myself,” she explains. It was not going to be easy.
Birth of a project:该项目被克里斯滕Kinolab, from the Greek wordkīnéō，意思是“举行动作”。随着KINOLAB网站解释的，它旨在成为“美国非商业用途的最富有，最全面的电影和系列剪辑，由学生和学者使用它的基础建造。”
作为一个适度的数字人文主义倡议，Kinolab收集了势头，后Cooper组装了一个项目团队，其中包括引导教师协作者费尔南多（数字和计算研究），开发商大卫弗朗西斯（学术技术和咨询），以及一部分的学生策展人Shani Agarwal ’20. In addition to overseeing the development of a tailor-made digital platform, Cooper has spent countless hours painstakingly seeking out film clips with her student curators, digitizing them, and tagging them with “data related to the aspects of film language or techniques that are illustrated in each clip,” she says.
The issue of copyright:这是必须克服的一个障碍。“没有啊,ne has done this type of thing before, so we needed to be careful with copyright issues and make sure we’re not abusing the ‘fair use’ doctrine” (which allows limited use of material without permission). The cause was helped in 2018 when the Library of Congress granted more freedom to use clips of films and TV shows for the purposes of criticism or commentary.
Some of the biggest challenges were technological，库珀说。“试图弄清楚如何建立我们需要的平台很难。It’s much more difficult to attach data to moving images than it is to static ones, because the things we’re interested in, like the close-up, the medium shot, and the reverse shot, for example, are embedded in time and space within the clip.”
How it works:
Kinolab是一个开放的项目, meaning anyone registered to the site is free to add annotated clips, although they have to be approved by one of the project’s curators. The initial content was mostly provided by Cooper and her students. To begin with, the clip database was quite “sci-fi heavy,” featuring excerpts from movies likeA.I. Artificial Intelligence,ex-machina,和Blade Runner,as well as TV shows like黑色镜子和Humans- 选择支持支持Bowdoin’s ethical computing initiative。然而，截至2021年2月，数据库已生长，以涵盖近20个类型，包括动画，宝莱坞，历史和惊悚片。
The COVID-19 pandemic库珀表示，已经将Kinolab转变为蜂巢的活动。“当它变得明显依赖遥控教学时，我们决定在夏天推出更新的平台，提前。”她描述了“令人兴奋和可怕”的推出。详情发布在社交媒体上，并被世界各地的电影学者拿起，包括教授凯瑟琳补助金在伦敦大学，将其描述为“必要的项目”。格兰特有这么多追随者，KinoLab被淹没在各地的请求中，解释了库珀。“我们试图在一个点注册它崩溃新平台的时候，我们必须转移到亚马逊服务器以应对卷。”
成长和合作：在过去的六个月里，Kinolab用户的数量已经四倍到了近400岁。也要感谢部分到这是一个开放项目的学术众群，数据库现在包含around 1,100 annotated film and TV clips。Furthermore, as Cooper notes, it has led to some interesting collaborations with other institutions, including Hamilton College, Colgate University, and others.
“One of the scholars we’re working with is Bruce Maxwell, director of computing programs and visiting professor of computer science at the Roux institute,” explains Cooper. Based in Portland, Maine, and part of Northeastern University, the罗克斯研究所专业从事人工智能的实际应用，为来自非CS背景的毕业生提供硕士和博士计划。去年推出了David Roux和他的妻子，芭芭拉的投资，两位P'14，他还为环境中资助了Bowdoin的Roux中心。
“Professor Maxwell does a lot with machine learning, where computers use neural networks to recognize patterns and draw their own conclusions.他和他的学生正在使用Kinolab数据集，以试图培训电脑来识别电影语言的各个方面,” says Cooper. Initially, the aim is to enable computers to identify close-ups. “Close-ups come in many different types, and they’re the most tagged aspect of film language on Kinolab.”
The goal, she adds, is eventually to explore other aspects of film language, but of course not all of them can be recognized by a machine. “For example, no computer will understand the difference between graphic blocking and social blocking,” says Cooper (referring to an aspect of filmmaking having to do with where actors position themselves in the shot). “Other aspects, however, such as the long shot, could feasibly be recognized by a computer.”
The future of Kinolab:进入Kinolab的越来越多的数据的前景表明，机器学习是前进的方向。“我们还没有那里，但希望有一天我们可以使用电脑在识别和标记电影和电视剪辑的山区时，我们可以使用计算机的大部分负担，”库珀说。“这将允许电影和媒体研究人员花费更少的时间准备诠释和更多时间解释数据。”与此同时，过去几个月的势头是指项目正在继续在快速剪辑中成长：“拥有的最佳问题，”库珀说。