Head Gesture Recognition System using Thermal Camera

IRJET, 2022

Hand Gesture recognition system is one of the best technique has developed in last few year, the reason behind to get success is ability to cooperate with machine. Body gestures are consider most common way to communication along human and personal computer in virtual world. To developed effective algorithm to that can recognize, interpret, process, and simulate human affections. Advance computing has ability to humanize digital interactions. This pepper introduces application using Computer Vision(CV) to recognize hand gesture. A camera takes live footage and analysis gestures on the basis of analysis system takes decision and recognize gestures.

IJIRMPS, 2020

This paper presents a recognition system, which can be helpful for a blind person. Hand gesture recognition system and face recognition system has been implemented in this paper using which various tasks can be performed. Dynamic images are being taken from a dynamic video and is being processed according to certain algorithms. In the Hand gesture system Skin color detection has been done in YCbCr color space and to discover hand convex defect character point of hand is used where different features like fingertips, angle between fingers are being extracted. According to gesture Recognized, various tasks can be performed like turning on the fan or lights. While in face recognition, Haar Cascade Classifiers and LBPH recognizer are being used for face detection and recognition respectively. With the help of OpenCV, The research has been implemented. Various hand gestures and human faces have been detected and identified using this system. The hand gesture was recognized with an accuracy of 95.2% was achieved and facial recognition was done with an accuracy of 92%.

2015

determines the location & size of human faces in digital images. Thus by determining the head gesture of person sitting on robo chair the controlling of the chair can be done by the improved Adaboost algorithm. The recognized gestures are used to generate motion control commands to the low-level DSP motion controller so that it can control the motion of the Robo Chair according to the user’s need. Looking for something, when the commands for the movement are generating must be considered unnecessary movement, thus to avoid this, Head gesture interface focused on the central position of a person sitting on robo chair & identify only the useful head gesture. This paper determines, the improved Adaboost algorithm used for face detection is to increase the output results for the system, effectiveness of the system & efficiency on which the system implements. The concept of Obstacle detection is also used for the enhancement of the system, it is done by using ultra sonic sensors.

2019 4th International Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU), 2019

In this paper, the hand gesture of a person is recognised and it identifies which hand of the person is raised. The skin colour is taken to recognise hands and face and the dark background is taken so that the skin detection may become easier. The hands and face are differentiated on the basis of area and centroid. Camera is the only input device used in this algorithm. No other input device is used to differentiate hands from the remaining body. This algorithm can be used both on the captured images and real time images.

2014

In this paper, we focus on using pointing behavior for a natural interface, Hand gesture recognition based human-machine interface is being developed vigorously in recent years. Due to the effect of lighting and complex background, most visual hand gesture recognition systems work only under restricted environment. To classify the dynamic hand gestures, we developed a simple and fast motion history image based method. In recent years, the gesture control technique has become a new developmental trend for many human-based electronics products. This technique let people can control these products more naturally, intuitively and conveniently. In this paper, a fast gesture recognition scheme is proposed to be an interface for the human-machine interaction (HMI) of systems. This paper presents some low-complexity algorithms and gestures to reduce the gesture recognition complexity and be more suitable for controlling real-time computer systems.

International Journal of Engineering and Technology

In this paper, Hand-Gesture Recognition System helps the dumb people finding difficult in communicating with the society. These people give some gestures to communicate with the normal people but all the gestures given by the dumb cannot be understood. So,there is a necessary to have some media between the dumb and normal people. The system recognizes the gestures given by the dumb and display the message on the LCD according to the gesture. The glove with flex sensors is worn to the hand of the dumb and when the gesture is given it is sensed by the flex sensor then the system recognize the gesture. Paraplegics are the persons whose body parts below the belly will not work and find difficulty in using the appliances. The system also consists of accelerometer control the fan and light. The appliances can be controlled by tilting the accelerometer. An alert message with the help of a GSM can be sent to the concerned person of the paraplegic when the paraplegic is in trouble.

— Gesture is a way of Human Computer Interaction. It is a technique that is mainly carried out to make impaired community communicate with normal humans. It's main aim is to convey human gestures to computing device. They are efficient for natural and intuitive human-computer interaction. To achieve this goal, computers should be able to visually recognize hand gestures from video input. We propose a new architecture to solve the problem of real-time gesture recognition. The fundamental idea is to use a combination of hand gestures to control various functionalities. This will include two parts, first is to track the movement of the hand and secondly is to track the orientation of the hand. This paper presents a robust and efficient technique for gesture recognition. The OpenCV library provides us a greatly interesting demonstration for object detection. Furthermore, it provides programs (or functions) that they used to train classifiers for their gesture detection system, called HaarTraining, so that we can create our own object classifiers using these functions. Our working environment is Visual Studio on Windows 7. The objective of this project is to develop an application for recognition of hand gestures with reasonable accuracy and thus creating windows media player compatible remote control.

IRJET, 2021

Smart wheelchair is a robotic system having the ability to navigate based on the Head gesture recognition technique. This smart system is controlled by various sensors and artificial intelligence techniques. The wheelchair can move forward, backward, left and right according to the directions from the ADXL 335 sensor which is controlled by the Arduino UNO. Tracking and monitoring the patients condition is made easier by making use of GPS and heartbeat sensors.

Pattern Recognition, 2006

For persons with severe disabilities who find it difficult to operate the joystick or the chin stick of an electric wheelchair, we have developed an interface that allows the wheelchair to be operated by gestures such as head movements. By using a camera to perform visual sensing, we aim to implement a non-contact non-constraining interface where no wires or equipment of any kind have to be attached to the user, thereby making the interface much more convenient to use. Range information obtained from a stereo camera is used to control the electric wheelchair in any situation regardless of whether it is used indoors or outdoors. We are keeping this study user-oriented by performing clinical trials with the help of actual users to determine where the camera should be situated, how it should be used, and so on.

Smart Innovations in Communication and Computational Sciences, 2018

Handbook of Research on Innovations in Information Retrieval, Analysis, and Management

This chapter presents the development of a new human-machine interface-a wheelchair controlled by the recognition of human hands' static gestures. The application will allow the occupant of an intelligent wheelchair to communicate with certain objects in order to facilitate their daily life. The suggested methodology draws on the use of computational processes and low-cost hardware. The development of the application involved dealing with computer vision issues in a comprehensive way. It was based on the steps of video image capture, image segmentation, feature extraction, pattern recognition and classification. In terms of its relevance and impact, the application described in the chapter promotes a more natural and intuitive mode of interaction for disabled individuals, which is expected to improve their quality of life.

Technology, which means the development and application of tools, machines, materials and processes that help to solve human problems, is a wonderful thing. With computers, all the information you could ever want is available on the Internet with a few keystrokes in a search engine. Technology has undoubtedly linked the world together, making it seem so much smaller and interconnected. A Human life getting improves by the use of a recent new application in the field of Human-Computer Interaction (HCI) and Computer Vision (CV). To deal with the versatile use cases is requiring the future desired Perceptual User Interfaces (PUI) and user interface devices for more reliable and fast performance. But this is the scenario for common people like us, physically challenged and mentally disabled are also important in our society. Hence such kinds need special kind of interfaces of interacting with system. The interface we propose is mouse, control by head movements and face gesture. In this survey paper we compare and contrast different algorithm and methods for detecting head movement. We study algorithm like Lucas-Kanade algorithm, Kalman filter algorithm etc. Devices like Gyrosensor, Accelerometer, Memes sensor etc.

2006

This project describes the motivation and design considerations of an economical head operated surveillance camera for people with disabilities. In addition, it focuses on the invention of a head-set operated device to control the movement of the camera, such that the camera can turn left and right according to the movement of the human head. It employs one tilt sensor, which placed in the headset to determine head position and to function as simple headset control system. The tilt sensor detects the lateral head motion to drive the left or right displacement of the camera. This system was invented to assist people with disabilities to live an independent life or even allow them to work as security personnel to earn their life. The idea can be employed in other application such as robotics, intelligent home devices and vehicle control as well.

2014

A recognition method for simple gestures is proposed and evaluated. Such gestures are of interest as they are the primitive elements of more complex gestures utilized in natural communication and human computer interaction. The input to the recognition method is obtained from a head tracker that is based on images acquired from a depth camera. Candidate gestures are detected within continuous head motion and recognized, acknowledging that head pose estimates might be inaccurate. The proposed method is evaluated within the context of human-computer dialog.The reported results show that the proposed approach yields competitive recognition results to stateof-the-art approaches.

International Journal of Computer Applications, 2013

Gesture was the first mode of communication for the primitive cave men. Later on human civilization has developed the verbal communication very well. But still nonverbal communication has not lost its weightage. Such nonverbal communication are being used not only for the physically challenged people, but also for different applications in diversified areas, such as aviation, surveying, music direction etc. It is the best method to interact with the computer without using other peripheral devices, such as keyboard, mouse. Researchers around the world are actively engaged in development of robust and efficient gesture recognition system, more specially, hand gesture recognition system for various applications. The major steps associated with the hand gesture recognition system are; data acquisition, gesture modeling, feature extraction and hand gesture recognition. There are several sub-steps and methodologies associated with the above steps. Different researchers have followed different algorithm or sometimes have devised their own algorithm. The current research work reviews the work carried out in last twenty years and a brief comparison has been performed to analyze the difficulties encountered by these systems, as well as the limitation. Finally the desired characteristics of a robust and efficient hand gesture recognition system have been described.