A Robust Bi-Directional Algorithm For People Count In Crowded Areas
This work addresses the need for reliable people counting in crowded places, such as building entrances, to aid in emergency management, but it appears incremental as it builds on existing blob-based methods.
The paper tackles the problem of accurately counting people in crowded areas by developing a robust bi-directional algorithm based on blob assessment to track inflow and outflow, achieving a system that can be used for real-time statistics and emergency response.
People counting system in crowded places has become a very useful practical application that can be accomplished in various ways which include many traditional methods using sensors. Examining the case of real time scenarios, the algorithm espoused should be steadfast and accurate. People counting algorithm presented in this paper, is centered on blob assessment, devoted to yield the count of the people through a path along with the direction of traversal. The system depicted is often ensconced at the entrance of a building so that the unmitigated frequency of visitors can be recorded. The core premise of this work is to extricate count of people inflow and outflow pertaining to a particular area. The tot-up achieved can be exploited for purpose of statistics in the circumstances of any calamity occurrence in that zone. Relying upon the count totaled, the population in that vicinity can be assimilated in order to take on relevant measures to rescue the people.