Securing public spaces is of vital importance for businesses and governments. Functioning security systems reassure customers, streamline public services, and ultimately protect both profits and people. However, guaranteeing that spaces remain crime and danger free means committing significant resources to surveillance and security staff. Monitoring security cameras requires patience, and round the clock attention and any lapses can be costly.
AI powered applications can help to sure up security systems and support staff. In order to achieve this developers need access to high quality image and video training data. This blog will focus specifically on key point annotation, and show how this particular annotation technique supports promising new security technologies.
Outsourcing this work to experienced annotation providers, like Keymakr, is a straightforward way of optimizing key point annotation for any project.
Key Points Definition
Key point annotation means marking salient or “key” locations on a given image with a dot using annotation tools. In the case of a human face this would mean identifying the location of eyes, noses, mouth etc. This technique can also be deployed in other images, for example pointing the important structural locations on an image of a building or a bridge.
Applications that benefit from key point annotation
Key point annotation is particularly useful for security AIs as it allows machine learning models to rapidly interpres human faces. This capacity enables a number of promising use cases:
- Facial recognition: Identifying individuals can be a powerful tool for protecting any public space. Annotation providers can produce images of faces in which the key points of the face are annotated. This labeled training data is then used by companies to create facial recognition machine learning models.
- Emotion recognition: Models are trained using large quantities of annotated images of faces. These labeled images help AI systems to recognize what kind of emotions are being expressed by an individual and whether this might prevent a potential threat. Problematic individuals can then be flagged for security to assess.
- Biometric passenger boarding: Biometric boarding means AI powered cameras identifying individuals by reference to key facial features, and other metrics such as height. By removing obstacles for passengers biometric identification systems are improving customer experience and reducing staffing needs as airports return to full operations. Key point annotation is central to all biometric identification AI models.
Getting the most out of key point annotation
Key point annotation is part of the growing revolution in AI for security. In order to realise the full potential of this annotation technique innovators are taking advantage of the expertise offered by professional annotation providers, like Keymakr. Here are three areas in which outsourcing keypoint annotation can provide an essential advantage:
- Annotating video: Annotating security footage with key points can be extremely time consuming. Locating correct point positions across thousands of frames represents a huge task for many organisations. Annotation providers can remove the burden of video annotation, making the process more efficient with the help of proprietary annotation tools.
- Management: Managing an in-house data annotation operation can be a distraction for security AI companies. Senior management and leading researchers can get bogged down with the everyday tasks of annotation administration. Outsourcing to experienced providers allows companies to avoid these drags on innovation, whilst allowing the provision of data to stay responsive to demands and troubleshooting.
- Security: When dealing with images of human faces it is vital that robust privacy and data protection processes are in place. It can often be confusing for AI companies trying to navigate available, legal data resources. Annotation experts can guarantee that all data being used meets the strictest standards for legality and security.
Keymakr makes use of proprietary annotation tools to create image and video training data that is precise and affordable.