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The expansion of internet technologies has led to challenges in managing and retrieving vast amounts of video content, causing information overload. Traditional search systems struggle to rank results based on user intent, prompting the research community to improve retrieval methods, notably through challenges like the Ho Chi Minh AI City Challenge. In this paper, we introduce KPI: Knowledge-based Processing for Interactive Video Retrieval, a novel system that enhances multimedia retrieval efficiency and accuracy. The system integrates text, automatic speech recognition (ASR), optical character recognition (OCR), and temporal retrieval, enabling time-based segment searches. Besides, we develop an elevated keyframe selection and incorporate a dominant-colour search strategy, all supported by a user feedback mechanism and a user-centric interface. Our system competes in the 2024 Ho Chi Minh AI City Challenge and achieves a competitive result.

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KPI: Knowledge-Based Processing for Interactive Video Retrieval

  • 会议论文

  • 发表日期：

    2025年

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  • Nhat-Sang Doan,
  • Minh-Duc Le-Ngo,
  • Khanh-Linh Bui-Le,
  • Duy-Ngoc Nguyen,
  • Minh-Quang Tran,
  • Trong-Tai Dam Vu,
  • Duc-Tuan Luu,
  • Vinh-Tiep Nguyen,
  • Minh-Triet Tran

摘要

The expansion of internet technologies has led to challenges in managing and retrieving vast amounts of video content, causing information overload. Traditional search systems struggle to rank results based on user intent, prompting the research community to improve retrieval methods, notably through challenges like the Ho Chi Minh AI City Challenge. In this paper, we introduce KPI: Knowledge-based Processing for Interactive Video Retrieval, a novel system that enhances multimedia retrieval efficiency and accuracy. The system integrates text, automatic speech recognition (ASR), optical character recognition (OCR), and temporal retrieval, enabling time-based segment searches. Besides, we develop an elevated keyframe selection and incorporate a dominant-colour search strategy, all supported by a user feedback mechanism and a user-centric interface. Our system competes in the 2024 Ho Chi Minh AI City Challenge and achieves a competitive result.