Suspicious Activity Detection using Machine Learning
Abnormal activity recognition and its detection becomes a major task in surveillance videos. From the context of security purposes, that it becomes more challenging to identify the suspicious events or activities in video surveillance. Surveillance closely observes, monitors and identify the behaviour of any object like people, suspicious thing or any abnormal activity. Technology is increases very fast, it becomes easier to identify and detect the abnormal activities. There are a lot of techniques and methods are available in field of detection of abnormal activities.
Abnormal Activity Detection is a crucial monitoring which is used to record anomalous human behavior without human efforts, the model has the ability to automatically take input video and live surveillance suspicious activity. The main objective is to automatically identify and mark occurrences that need human attention using Machine Learning and deep learning algorithms. The concept be applied to video surveillance system to quickly identify unusual activities. The model detecting on typical patterns of behavior in a given environment.
Suspicious Activity Detection using Image Processing
Software Requirements :-
- Coding Language : Python
- Implementation: Software Framework.
- Operating system : Windows 10 / 11.
- Graphical User Interface : Tkinter
Hardware Requirement:-
- Input Devices : Keyboard, Mouse.
- System : Pentium i3 Processor.
- Hard Disk : 500 GB.
- RAM : 4 GB.
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