If you list the biggest and fastest-growing technologies over the past decade, artificial intelligence (AI) will inarguably top the charts. The global AI market was valued at 39.9 billion in 2019 and is projected to grow at a CAGR of 42.2% during 2020-2027, according to Grand View Research.
AI has found applications in every industry, and the fitness sector is no different. Smart fitness wearables, AI-powered fitness apps, and AI and Machine Learning (ML) for gym management are common use cases of AI in fitness.
However not many people thought that there would come a time when AI would be on the verge of replacing personal trainers and fitness coaches. Yes, AI pose estimation technology has paved the way for AI-based fitness coach solutions.
Let’s delve deeper into AI pose estimation technology and how you can use it.
What Is AI Pose Estimation?
AI pose estimation is an application of Computer Vision(CV) technology that detects and infers the pose of a person or object in an image or video. You could also think of it as determining the camera’s orientation relative to the person or object in view.
The primary component of human pose estimation is the modeling of the human body. The solution identifies and tracks key points on the human body, such as the chin, elbow, knee, etc.
Types of Human Body Models
As discussed, a human pose estimation solution relies on the modeling of a human body. The technology mainly works on three popular human body models. These include:
- Skeleton-Based Model: This model comprises a set of joints (also known as key points), such as knees, elbows, chin, ankles, and other joints and areas that are a part of the human skeletal structure. A skeleton-based model can be detected from a 2D or 3D viewpoint by detecting and analyzing either X, Y coordinates or X, Y, Z coordinates of the body.
- Contour-Based Model: This model includes the rough width and contour of the human body, limbs, and torso. The person’s body parts are demonstrated using boundaries, along with rectangles to depict the silhouette.
- Volume-Based Model: This model consists of volume-based models with geometric shapes and meshes to present a person’s 3D human body share.
The following visual will give you a clear idea of how each human body model works.
How Does Human Pose Estimation Work?
An AI development company might use several ML-based algorithms for AI pose estimation. The primary human pose estimation techniques include deep learning architectures based on several Convolutional Neural Networks (CNNs). Bottom-up and top-down are two popular approaches used for pose estimation. Let’s discuss them briefly.
- Bottom-Up: In this approach, the human pose estimation solution first detects all the key points in the body and then assembles them into skeletons.
- Top-Down: In this approach, the model first draws a box around the human body or object using an object detector and then identifies and tracks the key points.
It’s essential to note that while 2D and 3D post-estimation may work on the same object, they have unique data requirements and produce different outputs. For example, 2D estimation produces 2D pixel values, whereas 3D estimation produces spatial arrangement. Therefore, each model is used to solve a specific problem.
Use Cases: Where is Human Pose Estimation Used?
Now that you know what AI pose estimation technology is and how it works, let’s look at some of its real-world use cases.
Tracking and measuring human activity and movements are the most popular applications of AI pose estimation. For example, you can point a camera at a person working out. A human pose estimation solution can detect the person’s movements and indicate if they’re doing it properly or not. This can be used for monitoring workouts (especially home workouts), workplace activity, and crowd counting.
- Animation and Gaming:
AI pose estimation technology and other deep learning (DL) approaches have streamlined character animation, which was once manual, bulky, and tedious. Now, character animation doesn’t require specialized suits or markers, as DL-based pose estimation automates the entire process.
Industrial robots have traditionally relied on 2D vision systems, which have several limitations. 3D pose estimation presents the opportunity to create more accurate, flexible, and responsive robotics systems.
- Augmented Reality (AR) Experiences:
Lastly, pose estimation technology can also help create more immersive and realistic AR experiences. As discussed, AI pose estimation isn’t limited to humans. It can also track objects, even those with non-variable key points. When blended with AR, pose estimation can be used to create more realistic simulated experiences.
How Can You Use Human Pose Estimation Technology?
The applications of AI pose estimation technology are surging, and it’s only the beginning. As the technology continues to grow, new applications will emerge. If you want to hop on to the pose estimation bandwagon and provide a unique experience to your consumers, now is the time. The technology has found uses in numerous sectors, such as:
The best way to use human pose estimation is to integrate it with your mobile app. The app can use the mobile camera for computer vision and analyze the user’s movements. Several startups have implemented AI pose estimation technology in their mobile apps. Some notable names include:
- Motion Coach
If you want to leverage pose estimation, choose to work with a leading AI development company, Quytech. The experts here understand your requirements and come up with an effective strategy to develop and implement a human pose estimation solution in your business.
The use of AI pose estimation technology is increasing, especially in the fitness sector, as more people are working out in their homes. The technology is still in its early stages, with a massive scope of development and application. However, since the concept of pose estimation is new, not many companies are accustomed to using it. Therefore, it’s crucial to work with an expert AI development company like Quytech to build a robust human estimation solution for your business. They are recognized as leaders in providing robust and scalable mobile applications in the healthcare and fitness industry.