Object Recognition, Security AI and Data Annotation

Object Recognition, Security AI and Data Annotation

Powerful, observant and consistent security systems are essential for keeping public areas and businesses safe. Detecting violent threats, dangerous objects and potential theft early helps to protect these spaces. This has traditionally been the job of security staff, who monitor security camera footage.

However, security teams are now being supported by computer vision AI. Object recognition is an AI application that is particularly useful for security systems. Because of the potential of object recognition in this sector, security AI companies are looking for high quality image and video annotation for AI training.

This blog will first show how automation and object recognition can help to improve security. Secondly we will identify some of the most promising applications that use object recognition. And finally we will reveal how AI developers can access high quality training datasets.

The potential of automated security systems

Humans must monitor traditional security systems at all times. This requires multiple staff members to watch security camera feeds sometimes 24/7. Additionally gaps in staffing can lead to gaps in coverage. Similarly, it can be difficult for humans to maintain the concentration required to attentively observe multiple camera feeds over a long shift.

Consequently engineers design security AIs to help staff by maintaining constant background surveillance. Object recognition capabilities support security systems by alerting staff and law enforcement agencies when a problematic object is identified. AI can catch things that slip through the security net and therefore should form part of any integrated security system.

Video annotation
Video annotation | Keymakr

Object recognition applications

Object recognition is a key capability of security AI systems. Computer vision models are able to identify objects from digital images and create alerts based on the information they see. Object recognition makes the following applications possible:

  • Identifying weapons: It can be difficult for humans to recognise weapons on small or low resolution security feeds. Alternatively security may not be monitoring cameras when a weapon is present. Object detection AI can immediately locate a gun or a knife in an image and quickly inform staff who can respond appropriately.
  • Locating suspicious objects: Public spaces can be targets and need protecting as such. Explosive or otherwise dangerous devices can be left in hard to spot places that humans might miss. AI security systems can constantly scan spaces and identify unusual objects that might be worthy of further investigation.
  • Loss prevention: Object recognition can also be used to prevent theft. By locating objects, such as bags or valuable products, in images security AI systems can give alerts when they are taken.
  • Airport security: Object recognition is also essential for security AI in airports. This capability allows automated systems to identify bags on security carousels and in terminals. This ability to distinguish between harmless objects and potentially dangerous ones helps to support airport security personnel.
Object detection

High quality annotation for security AI

Object recognition for security AI is only possible with the help of precise image and video annotation. Keymakr is a data annotation provider that offers important advantages to developers in this sector:

  • Video annotation: Keymakr’s annotation platform is designed with video annotation in mind. Object interpolation tools and task sharing options ensure that video annotation projects are completed on time.
  • Secure data: Training data for security AI applications can contain sensitive images and video that need to be kept private. Keymakr uses encryption, data expiration and VPNs to keep data safe.
  • Data collection: Keymakr are experts in data collection. Our team uses publicly available data pools to create powerful datasets. Our collection expertise removes a burden from busy AI developers.
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