Intuitive air gesture recognition system for dynamic computer interaction

Abstract

A gesture-based system for computer interaction, characterized in that the system includes the following: a camera to capture the image of a gesture; a sensor for detecting movements in a user's limbs; a microcontroller that includes several modules: an image preprocessing module for preprocessing the images captured by the camera; a gesture recognition module for recognizing the gestures of the user's limbs detected by the sensor; a hand validation module for identifying hand presence; a palm rejection logic module for palm recognition; a gesture recognition engine for classifying gestures and handling unrecognized gestures; a command execution framework module for translating gesture commands; a user feedback mechanism module for providing usage feedback; A system condition assessment module for evaluating the system condition.

Description

[0001] In a digital world, gestures play a crucial role in human-computer interaction. These gestures can be used to interact with systems such as video games, UAVs, medical devices, and more. Intelligent systems exist that require the reading of gestures for dynamic computer interactions, particularly for people with disabilities. Traditional systems require physical contact during interaction, which is insufficient for people with disabilities. Therefore, understanding the gestures of people with disabilities and adapting them for computer use is essential. However, existing technologies have limitations. For example, the Leap Motion Controller, a hand gesture recognition device that enables gesture control of computers, requires a physical hardware component.Existing art installations have camera systems that can recognize some hand gestures. A conventional Kinect sensor can recognize some hand gestures for basic interactivity.

[0002] The problem is solved by the features listed in claim 1.

[0003] The purpose of the invention is achieved by disclosing a gesture-based system for computer interaction. The system comprises a camera for visually capturing a gesture; a sensor for detecting movements in a user's limbs; and a microcontroller integrated with a variety of modules. These modules include, among others, an image preprocessing module, a gesture recognition module, a hand validation module, a hand rejection logic module, a gesture recognition engine, a command execution framework module, a user feedback mechanism module, and a system state evaluation module.

[0004] The image preprocessing module is configured for preprocessing the images captured by the camera.

[0005] The gesture recognition module is configured to recognize gestures of the user's limbs detected by the sensor.

[0006] The hand validation module is configured to detect the presence of a hand.

[0007] The palm rejection logic module is configured to recognize palms. The gesture recognition engine is configured to classify gestures and handle unrecognized gestures. The command execution framework module translates gesture commands. The user feedback mechanism module provides usage feedback. The system health assessment module evaluates system health.

[0008] The device consists of the hand. The system recognizes individual alphabet gestures. The system includes the mapping of specific alphabet gestures. The system includes air mouse control through gesture recognition to enable users to navigate and interact with the computer interface.

[0009] The present disclosure also discloses a method that incorporates real-time gesture recognition. This includes capturing hand movements with a camera or sensor, processing the visual data using an advanced algorithm to identify specific gestures, and mapping these gestures to predefined computer functions or commands. This method revolutionizes traditional computer interaction and provides a more intuitive and engaging user experience. The system's adaptability to varying lighting conditions ensures reliable performance in diverse environments.

[0010] The advantages of the present disclosure are as follows: 1. Use of machine learning: The use of machine learning models for the detection and recognition of complex hand gestures, as opposed to conventional methods of geometric or template matching, makes the invention less obvious. Machine learning enables more accurate and robust gesture recognition. 2. Specific alphabet gesture recognition: The ability to recognize individual alphabet gestures, as opposed to just a few generic gestures, increases the complexity and utility of the system. This level of granularity in gesture recognition is not immediately obvious. 3. Gesture-to-Application Mapping: Assigning specific alphabet gestures to launch corresponding applications based on their initial letters provides an intuitive and convenient user experience. This gesture-to-application mapping is a less obvious feature. 4. Air Mouse Functionality: Providing air mouse control through gesture recognition, which allows users to navigate and interact with the computer interface, offers significant added value. This improvement is not a straightforward extension of basic gesture recognition. 5. Improved accessibility: The invention aims to provide an accessible and intuitive computer control system for users with disabilities or those who prefer gesture-based interaction. This accessibility goal is not immediately obvious from the combination of features in the invention.

Claims

[1] A gesture-based system for computer interaction, characterized by that the system includes: a camera to capture the image of a gesture; a sensor for detecting movements in a user's limbs; a microcontroller that includes several modules: an image preprocessing module for preprocessing the images captured by the camera; a gesture recognition module for recognizing the gestures of the user's limbs detected by the sensor; a hand validation module to identify hand presence; a palm rejection logic module for detecting palms; a gesture recognition engine to classify gestures and handle unrecognized gestures; a command execution framework module for translating gesture commands; a user feedback mechanism module for providing usage feedback; a system health assessment module for assessing the system health. [2] System according to claim 1, characterized by that the member encompasses a hand. [3] System according to claim 1, characterized by that the system recognizes individual alphabet gestures. [4] System according to claim 1, characterized by that the system includes the mapping of certain alphabet gestures. [5] The system according to claim 1, characterized by that the system includes air mouse control through gesture recognition to enable users to navigate and interact with the computer interface.