← 返回论文检索
ACM Multimedia 2025Experience: Multimedia Applications

VisAug: Facilitating Speech-Rich Web Video Navigation and Engagement with Auto-Generated Visual Augmentations

Baoquan Zhao, Xiaofan Ma, Qianshi Pang, Ruomei Wang 0001, Fan Zhou 0001, Shujin Lin

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.1145/3746027.3754584 ↗

摘要

The widespread adoption of digital technology has ushered in a new era of digital transformation across all aspects of our lives. Online learning, social, and work activities, such as distance education, videoconferencing, interviews, and talks, have led to a dramatic increase in speech-rich video content. In contrast to other video types, such as surveillance footage, which typically contain abundant visual cues, speech-rich videos convey most of their meaningful information through the audio channel. This poses challenges for improving content consumption using existing visual-based video summarization, navigation, and exploration systems. In this paper, we present VisAug, a novel interactive system designed to enhance speech-rich video navigation and engagement by automatically generating informative and expressive visual augmentations based on the speech content of videos. Our findings suggest that this system has the potential to significantly enhance the consumption and engagement of information in an increasingly video-driven digital landscape.