Meetor: A Human-Centered Automatic Video Editing System for Meeting Recordings

Author:

Duan Haihan123ORCID,Liao Junhua4ORCID,Lin Lehao2ORCID,El Saddik Abdulmotaleb35ORCID,Cai Wei2ORCID

Affiliation:

1. Shenzhen MSU-BIT University, Shenzhen, China

2. The Chinese University of Hong Kong, Shenzhen, China

3. Mohamed bin Zayed University of Artificial Intelligence, Masdar City, United Arab Emirates

4. Sichuan University, Chengdu, China

5. University of Ottawa, Ottawa, Canada

Abstract

Widely adopted digital cameras and smartphones have generated a large number of videos, which have brought a tremendous workload to video editors. Recently, a variety of automatic/semi-automatic video editing methods have been proposed to tackle these issues in some specific areas. However, for the production of meeting recordings, the existing studies highly depend on extra equipment in the conference venues, such as the infrared camera or special microphone, which are not practical. In this article, we design and implement Meetor, a human-centered automatic video editing system for meeting recordings. The Meetor mainly contains three parts: an audio-based video synchronization algorithm, human-centered video content flaw detection algorithms, and an automatic video editing algorithm. Two main experiments are conducted from both objective and subjective aspects to evaluate the performance of the Meetor. The experimental results on a testbed illustrate that the proposed algorithms could achieve state-of-the-art (SOTA) performance in video content flaw detection. However, the conducted user study demonstrates that Meetor could generate meeting recordings with a satisfactory quality compared with professional video editors. Moreover, we also present a practical application of the Meetor in a university campus prototype, in which the Meetor is applied in the automatic editing of lecture recordings. All in all, the proposed Meetor can be utilized in practical applications to release the workload of professional video editors.

Funder

Shenzhen Science and Technology Program

Guangdong-Hong Kong-Macao Joint Laboratory for Emotional Intelligence and Pervasive Computing, Artificial Intelligence Research Institute, Shenzhen MSU-BIT University

National Natural Science Foundation of China

Publisher

Association for Computing Machinery (ACM)

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