Factors Influencing Real-Time Violent Behavior Recognition : A Review

ABSTRACT: Real-time violent behavior recognition is pivotal for enhancing public safety by enabling prompt detection and intervention in potentially dangerous situations. This review comprehensively examines the factors influencing the effectiveness of real-time recognition systems. We discuss the essential role of real-time recognition in improving security measures and highlight critical factors affecting system performance. Key areas covered include the quality and diversity of datasets, which are crucial for training robust models; the design of model architectures, which impacts the balance between computational efficiency and recognition accuracy; and the constraints imposed by computational power, memory, and network bandwidth. By analyzing these factors, this review provides insights into the current challenges and advancements in real-time violent behavior recognition, offering a foundation for future research and development aimed at enhancing system performance and reliability.