A Review on Real-Time Person Detection and Description Systems
Year: 2025
Type: conference-paper
Abstract: Advancements in surveillance technologies are pivotal in addressing the growing demands for real-time monitoring and actionable insights across industries such as security, public safety, and traffic management. This review explores existing research and technologies in real-time person detection, attribute analysis, and semantic description generation, highlighting their applications, limitations, and gaps. It further presents a novel system integrating YOLOv8 for object detection, OpenCV forattribute analysis, and Qwen2VL for vision-language tasks, addressing key challenges such as latency, scalability, and dynamic environment adaptability. Future directions include integrating emotion recognition, multilingual GUIs, and predictive analytics to enhance system utility and versatility.
Authors: Kapur, Mokksh, Goswami, Puneet
Institution: SRM University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6949290788
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