AI Based Gesture Recognition Solutions – Overview
- Gesture recognition enables silent, body-only communication between humans and machines.
- There is a natural and instinctive approach to communicating with others and our environment through gestures. Therefore, interfacing with a computer through hand gestures makes perfect sense.
- But there are many difficulties, ranging from the need to wave your hands in front of the tiny screen of your smartphone and ending with the complex machine learning algorithms needed to understand gestures other than a basic thumbs-up. Does the juice justify the effort? Let’s take a look, starting with the terminology and moving on to the specifics of the technology.
AI Gesture Recognition: How Does It Work?
- Gesture recognition gives real-time information to a computer so that it can carry out user commands. Gestures can be tracked and interpreted by motion sensors in the device, making them the main source of data input.
- in bulk gesture recognition technology Combine infrared and 3D depth-sensing cameras with machine learning technology. Machine learning algorithms can distinguish hand and finger postures because they have been taught using labeled depth images of hands.
There are three basic layers of gesture recognition:
Search – a machine learning techniques Segments the image after the camera detects hand or body movement to identify the edges and position of the hand.
to keep track – A device tracks motion frame by frame to record each movement and provide accurate data for data processing.
Recognition , Based on the collected data, the system tries to identify trends. When the system detects a match and understands the gesture, it executes the action associated with the gesture. The recognition functionality is implemented in the following scheme through feature extraction and classification.
Source: Research Gare
- For hand tracking, many solutions use vision-based systems, although this method has several drawbacks. These systems struggle when hands overlap or are not clearly visible because users must move their hands inside a confined space. Although, gesture recognition system Can recognize both static and dynamic motion in real time when using sensor-based motion tracking.
- Depth sensors are employed in sensor-based systems to realistically line up computer generated images. The number and three-dimensional position of the fingers, the center of the palm and the direction of the hand are detected by the Leap Motion sensor as part of hand tracking.
The processed data provides information on a variety of topics, including the angle of the fingers, separation from the center of the palm, height, and coordinates in three dimensions. Depth and jump motion sensor data are used to train algorithms used in hand gesture recognition systems for image processing.
- Using color and depth information, the system can separate the hand from the surrounding area. The hand, wrist, palm and fingers are further separated from the hand model. Since the hand and wrist do not contain gesture information, the algorithm ignores them.
- The system then collects data on the shape of the palm, the location of the fingers, the height of the fingers, the distance between the fingers and the center of the palm, and other factors.
- The system then compiles all the features it has retrieved into a feature vector that represents a gesture. AI-based hand gesture recognition software Compares feature vectors to a database of different motions to identify user gestures.
Because depth sensors enable users to discard specialized wearables such as gloves and make HCI more natural, they are essential for hand tracking technologies.
How we developed an AI based gesture recognition solution for a start-up firm.
- OptiSol helped a startup company build an AI/ML-based solution approach that helps non-technical users record sign translations of Bible verses.
- This application allows sign language experts to log into a web portal and use gesture recognition.
- This platform is used by non-technical people to record sign language translations of Bible verses.
- Then use the data to train a gesture recognition model to interpret and translate the Bible version from sign language gestures.
- The platform focuses on the need to reach out to sign language users and give them the opportunity to read and interpret Bible verses.
- Ability to easily translate sign language gestures of Bible verses into multiple international languages.
Market Size: Gesture Recognition
The gesture recognition market size was estimated to be USD 14.08 billion in 2021 and is expected to grow at a compound annual growth rate (CAGR) of 19.1% from 2022 to 2030.