Crowd detection and management using cascade classifier on ARMv8 and OpenCV-Python

The steady increase in population and overcrowding has become an unavoidable factor in any public gathering or on the street during any festive occasions. The intelligent monitoring technology has been developing in recent years and human tracking has made a lot of progress. In this paper, we propos...

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Veröffentlicht in:ICIIECS '17 : proceedings of 2017 International Conference on Innovations In Information, Embedded and Communication Systems : Coimbatore, India, 17th 7 18th March 2017 S. 1 - 6
Hauptverfasser: Abbas, S. Syed Ameer, Jayaprakash, P. Oliver, Anitha, M., Jaini, X. Vinitha
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.03.2017
Schlagworte:
Adaboost algorithm
Cameras
cascade classifier
Haar features
Head
head detection
Magnetic heads
Streaming media
Tracking
Training
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Zusammenfassung:The steady increase in population and overcrowding has become an unavoidable factor in any public gathering or on the street during any festive occasions. The intelligent monitoring technology has been developing in recent years and human tracking has made a lot of progress. In this paper, we propose a method to manage the crowd by keeping in track the count of the people in the scene. In our study, we develop a system using Raspberry Pi 3 board that consists of ARMv8 CPU that detects the human heads and provide a count of humans in the region using OpenCV-Python. A Haar cascade classifier is trained for human head detection. Human tracking is achieved by indicating the direction of movement of the person. The results of the analysis will be helpful in managing the crowd in any area with high density of crowds.
DOI:10.1109/ICIIECS.2017.8275988