Pose and movement detection

The rapid development of technology leads to the emergence of innovative solutions that greatly simplify the lives of ordinary users and large companies.

Artificial intelligence (AI) is being actively implemented in many areas, including medicine, industry, entertainment and, of course, business.

Today, neural networks can not only entertain, but also heal, teach and work. Their potential makes it possible to accurately detect human movements and postures, for example, for creating 3D models or studying sign language.

Human posture detection is a computer vision-based technology that detects and analyzes the position of the body in space. The pose is assessed by modeling the human body.

There are three most commonly used types of detection models:

• Skeleton-based: is a collection of key points (joints) such as ankles, knees, elbows, etc. that form the skeletal structure of the human body. Due to its flexibility, this model is often used in 2D and 3D posture estimation techniques.
• Outline Based: Consists of an outline, the approximate width of the torso and limbs.
• Volume-based: Consists of three-dimensional human body shapes and poses represented by volumetric models with geometric meshes.

The first model of posture detection, in which the system relies on key points on the body, arms, legs and face of a person, is one of the most common. The more precisely the markers are positioned, the better the result for applying the corresponding model (depending on the subject area, for example, for hands, head or legs).

Assessment of human posture in video plays an important role in software development, for example, technology allows digital content to be superimposed on top of the physical world in augmented reality, to recognize sign language and control movements.

In addition, its capabilities help define exercise, which can be the foundation of applications for learning dance, yoga or fitness.

In order to better understand how the software for detecting postures and movements works, consider an example – a fitness application. The system operates as follows:

1. Recording of human movements during exercise.
2. Analysis of the correctness of the exercise.
3. Identifying and displaying errors in the user interface.

Such programs are based on artificial intelligence and machine learning – the ability of a system to independently solve various problems and interpret experience for improvement. During training, the AI ​​processes huge amounts of information, studies and finds certain patterns in them.

An example is Mirror, a machine learning-based software that analyzes the user’s movements and, based on preferences and goals, provides them with real-time feedback. The Motion Coach app uses computer vision and a phone camera to provide audible cues and visual feedback as you work out, while Fitness Ally by TwentyBN includes a virtual fitness trainer that “oversees” exercise.

The AVADA MEDIA team develops complex IT solutions for business process automation, information security, data analytics, etc. Our specialists design reliable software, including software for detecting postures and movements.

The number of artificial intelligence technologies and applications continues to grow rapidly. Its potential allows you to constantly interact with a changing environment with a huge number of variables. Pose detection helps to estimate the spatial position of the body in video or images, so the technology can be used to predict and track the location of a person or object.

There are several areas in which the detection of postures and movements is used:

• Tracking and measuring human activity is one of the areas where motion detection is most commonly used. Examples include applications for analyzing dance and sports techniques, exercise performance, and security and surveillance applications.

The technology is driving the emergence of artificial intelligence-based virtual trainers that test how people are doing exercises correctly and whether they need instructions to change their body position.

• In augmented and virtual reality, pose assessment improves the user experience of interacting with objects. For example, it helps you learn how to play games like tennis virtually.

Pose detection software can replace the expensive motion capture systems used in film and video game production.

• Teach and train robots – technology allows machines to learn to solve specific problems and master the work. To do this, the human instructor demonstrates certain actions, and the robot reads them and repeats.
• An unusual application of the technology is tracking people’s movements in interactive games. For example, Kinect uses 3D pose estimation (thanks to data from special sensors) to detect player movements and use them to visualize the actions of virtual characters.

These capabilities are not exhaustive – as artificial intelligence becomes more popular and in demand, companies are finding new ways to use it in various industries.

AVADA MEDIA specialists create flexible software in accordance with the needs and specifics of the company, which helps the business to establish communication with customers, effectively scale and increase revenues.