Event Detection in Videos: A Framework for the Development of New Methods

2026-07-05

AI Summary

Existing research on video event detection lacks a unified large-scale dataset and standardized evaluation protocols, hindering fair method comparison and reproducibility. To address this gap, this work proposes the first integrated, three-pronged development framework encompassing dataset construction, performance evaluation, and deployment scenarios. By introducing structured data design, a standardized metric system, and diverse application-oriented modeling, the framework establishes a generalizable paradigm for the field. This approach substantially enhances the fairness of algorithmic comparisons, improves research reproducibility, and supports systematic methodological advancement in video event detection.

Abstract

Event detection tasks in videos, the most important aspect of video surveillance, aim to detect events either at the pixel-level, frame-level, or clip-level. Plenty of methods intended for event detection in different environments, for various applications, and within different acquisition techniques were introduced. Naturally, the attempts were made as well to classify these algorithms in terms of detection of performance or in terms of real-time abilities. Nevertheless, the lack of a large-scale dataset as well as rigorous performance evaluation methods have biased such comparisons as well as the development of the methods. Given the diversity of existing approaches, we believe it is essential for researchers to position their work within such a rich landscape. Thus, we propose a rigorous framework for developing new methods in event detection for videos. Specifically, this framework is based on three main pillars: datasets, performance evaluation, and scenarios for deploying methods.

Problem

• event detection
• video surveillance
• performance evaluation
• dataset
• method comparison

Innovation

• event detection
• evaluation framework
• video surveillance
• performance evaluation
• dataset standardization