AI-Powered Short Video Analytics

Abstract:

The rapid proliferation of short video platforms has generated vast amounts of visual content, presenting opportunities for video analytics. This project, AI-Powered Short Video Analytics, utilizes state-of-the-art computer vision and machine learning techniques to extract meaningful insights from short video data. Its purpose is to employ automated tools to quantify multimodal features and assess their impact on video engagement or product sales. The key research questions include: How can AI models effectively analyze and categorize short videos? Can automated analytics improve content creation on short video platforms?

Note: Professor Yulin Fang (ylfang@hku.hk) will serve as the project’s co-mentor.

Skills and experience required for the project:

Students with a background in Computer Science, Data Mining, or related disciplines are preferred. Ideal candidates should possess strong programming skills and have experience with computer vision techniques, such as OpenCV or deep learning frameworks. Experience in web or social media data crawling is also highly desirable.