An Efficient System for Pedestrian Detection from Video Sequences

Pedestrian detection from video sequences is a computer vision task that involves identifying and locating pedestrians in a series of frames from a video. This task is crucial for various applications, including video surveillance, autonomous vehicles, and advanced driver assistance systems (ADAS). Considering security concerns have developed in recent days, detection of pedestrians, following, and unusual behavior recognition have become more vital in applications that utilize computer vision. Engaged video surveillance technology that can follow pedestrian behavior in real time is necessary since it is extremely challenging to continuously track public as well as private spaces in high-density locations. The issue of pedestrian detection in video sequences is addressed in this paper. An essential part of the driver assistance system is the pedestrian detection system. Intelligent video surveillance, intelligence, and transportation all frequently use pedestrian detection and tracking. The system can function in real time and has a high recognition accuracy, according to experiments. The idea can be applied to keeping things hygienic, preserving database memory, and counting the number of people who have achieved fame. The exploration of new research avenues in vision-based monitoring for both professionals and scholars served as the paper's conclusion.