Due to the drastic rise of criminal and violent activities across the workplace and unexpected fights, businesses insist on using surveillance to figure out the level of danger. Installing a video surveillance system to detect violent interactions is also suitable for law enforcement agencies.
- The surveillance videos record human activities intensely and have emerged as a preferred area of research and Artificial intelligence, machine learning.
- The video displays violent human behavior and normal activities, such as running, eating, lying on the bend, sitting on the chair, descending chairs, and various other options.
- The violent activities are abnormal and inflict harm or damage with an aggressive approach.
- Some of the violent activities taking place in public places are beating someone, fighting, and killing.
- While the semi-automatic equipment leverage manual monitoring through a screen or surveillance camera, the fully automated systems detect human activities through Artificial intelligence, machine learning, and computer vision technology.
- Violent incidents are typically unexpected, and may occur at any time, so there is no opportunity of misjudging the right thing to do to prevent harm.
- The fully automated systems are more effective for detecting human activity when compared with the semi-automatic equipment.
- Inconsistency of light, and poor video quality of the cameras is a couple of challenges that may deter the quality of the images.
- The recognition of action is one of the areas where computer vision technology specializes in the modern world.
- The recognition of violent action is essential to eliminate safety, and security threats.
Detecting suspicious activities is entirely different from violence detection, as the latter may begin at any location.
Using ML for violence detection:
The incidents of violence in crowded places are fast becoming normal, and posing a major threat to the stability, security, and uncertainty in everyday life. However, with the violence & fight detection device based on machine learning, the aim is to automatically determine whether the violence occurs or not.
- It is highly challenging for humans to record the videos as most of the violent incidents occur suddenly.
- The progress in computer vision technology, and Artificial intelligence, machine learning allow people to surpass the limitations of humans.
- The violent incidents may involve firearms, explosions, or gunshots, so automated software recording the violent incidents provide the best clue.
Undoubtedly, the reliance of humans on fully automated systems for violence, and fight detection is one of the milestones of the modern age.
The takeaway:
The growth of surveillance cameras to track human activity has reached a new limit. Therefore, the automated system recording the violence, and suspicious events is one of the most successful research-based areas of recent times. The trends of violence have undergone a massive change during recent times, so the detection technique needs to be top-grade.
For detecting violent behavior with the highest accuracy, you need to check whether the dataset delivers accurate results in real-time. Therefore, computer vision technology must be reliable, and established. Artificial intelligence, machine learning, and deep learning are fast becoming the preferred approaches to detecting violence.
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