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A Survey on Visual Analytics for Intelligent Video Understanding and Analysis
PhD Qualifying Examination Title: "A Survey on Visual Analytics for Intelligent Video Understanding and Analysis" by Miss Jianben HE Abstract: Video, as a versatile multimedia format, has become the most prevalent transmission and communication channel these years. A huge amount of videos are being generated every day on various video platforms such as YouTube and TikTok. Efficient video exploration and analysis have been crucial for many applications including business, security, and edu- cation. Recently, taking advantage of the powerful computational resources, massive works in the computer vision field are trying to leverage machine learning algorithms to auto- matically summarize and analyze videos. However, these techniques are usually facing the challenges like semantic information deficiency and cross-modal fusion problems due to the inherent complexity of video data. Moreover, these automated methods fail to provide flex- ible interactions for users to comprehend and reason about the analysis process and results. Visual analytics, which combines the strength of both machine and human intelligence, has been introduced to enable better summarization, exploration, and augmentation of videos with intuitive representations and rich interactions. This survey aims to give a systematic overview of how the existing works in the visu- alization community tackle the challenges of video analysis. We start with an introduction to our proposed taxonomy. Then we digest the state-of-the-art works within three catego- rized goals: video visual representation, video visual pattern discovery, and video visual augmentation. Finally, we discuss the future research challenges and opportunities. Date: Monday, 4 October 2021 Time: 4:00pm - 6:00pm Zoom meeting: https://hkust.zoom.us/j/2187438010 Committee Members: Prof. Huamin Qu (Supervisor) Prof. Qian Zhang (Supervisor) Dr. Xiaojuan Ma (Chairperson) Dr. Dan Xu **** ALL are Welcome ****