Body Pose Detection App using Google ML-Kit Flutter

Human posture is an important body part that indicates the fundamental structure of the human body. ML Kit Pose Detection doesn’t require specialized equipment or ML expertise in order to achieve great results. With this technology, we can create one-of-a-kind experiences for the users.

ML Kit Pose Detection produces a full-body 33-point skeletal match that includes facial landmarks (ears, eyes, mouth, and nose) and points on the hands and feet. The user’s face must be present in order to detect a pose. Pose detection works best when the subject’s entire body is visible in the frame, but it also detects a partial body pose. The aim of our flutter-based Body Pose Detection System using Google ML-Kit is to develop an application that can analyze the human body posture by capturing an image of the body and providing the details of it.

This project is written in Dart and the database used is SQLite, and it is based on the flutter framework. Dart is a programming language that Google developed and keeps up with. A cross-platform framework for building high-performance mobile apps is called Flutter.

In this system, the user can upload an image from their phone’s gallery or capture a photo. From the static image, the system will detect the body posture with the details. Here, there is also another option available, a real-time camera. The user can open their phone’s camera to see the body posture in real-time. The system will display the posture details to the user. The ML Kit Pose Detection API is a lightweight versatile solution to detect the pose of a subject’s body in real-time from a continuous video or static image.

A pose describes the body’s position at one moment in time with a set of skeletal landmark points. The landmarks correspond to different body parts such as the shoulders and hips. The relative positions of landmarks can be used to distinguish one pose from another.

Advantages

• It is easy to maintain.
• It is user-friendly.
• The user can easily detect body posture details from an image.
• Also, real-time body pose detection is also available.