Gesture Recognition System

2011

Human-Computer Interactions (HCI) makes computers more usable and receptive to user’s needs by improving the interactions between humans and computers. Current HCIs use keyboards, mice, joysticks and touch-screens as user interface. However, such mechanical devices are inconvenient for natural and direct interactions, whereas, the human gesture allows users to communicate with machines in a natural way. Among the available gestures for Gesture Recognition System (GRS), hand gestures are the most powerful means of communication and they find their application in educational institutions and entertainment. In the current paper, a GRS has been designed and developed for file browser application. The GRS system mainly consists of a Transmitter module and a Receiver module. The transmitter module consists of a camera, a DSP processor and a wireless RF transmitter. The receiver module consists of a wireless RF receiver, an embedded processor and a LINUX machine. The image acquired through...

This paper presents simple as well as effective methods to realize hand gesture recognition. Gesture recognition is mainly apprehensive on analysing the functionality of human Intelligence. The main aim of gesture detection and recognition is to design an efficient system which is able to recognize particular human gestures and use these detected gestures to transfer information or for controlling devices. Hand gestures enable a vivid complementary modal to communicate with speech for expressing ones thought of idea. The information which is associated with hand gestures detection in a conversation is extent or degree, detection discourse structure, spatial and temporal design structure. Based on the above given points the paper discusses various models of gesture detection and recognition.

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.

Journal of Telecommunication, Electronic and Computer Engineering, 2018

The concept of hand gesture recognition has been widely used in communication, artificial intelligence, and robotics. The most contributing reason for the emerging gesture recognition is that they can create a simple communication path between human and computer called HCI (Human-Computer Interaction). Therefore, a hand gesture recognition algorithm was developed for fourteen hand gestures based on finger counting. The algorithm counts fingers and recognizes gesture based on the maximum distance between the fingers detected. The algorithm divided into four main parts: image acquisition, pre-processing, finger detection, and gesture recognition. The experimental results show that the algorithm can count fingers accurately and recognize 10 gestures (associated with 1, 2, 3 and 5 fingers) with good performance (70 to 100 percent of successful detection) and 4 gestures (associated with 4 fingers) with average performance (50 to 70 percent of successful detection). Additionally, the algo...

The task of gesture recognition is highly challenging due to complex background, presence of nongesture hand motions, and different illumination environments. In this paper, a new technique is proposed which begins by detecting the hand and determining its canter, tracking the hands trajectory and analyzing the variations in the hand locations, and finally recognizing the gesture. The proposed technique overcomes background complexity and distance from camera which is up to 2.5 meters.

Hand gesture recognition in aspect to human-machine interface is being developed vastly in recent days. Because of the disturbance of lighting and background being not plain, many visual hand gesture recognition systems operate or show successful results only in restricted background. To recognize the various hand gestures, we will build a non complex and with greater speed motion history image related system. In our system, we mainly focus on applying pointing behavior for the human machine interface. Now days, the gesture recognition has been a new developmental and experimental thing for most of the human related electronics. This system allows people to operate electronic products more conveniently. In our system, a gesture recognition method is to be build which will be an interface between human machine interaction i.e. HMI. In our system we propose some non-complex algorithm and hand gestures to decrease the hand gesture recognition complexity and would be more easy and simpl...

IJRCAR, 2013

The recent progress on human- computer interface technology has enabled more intuitive and natural communications between human and sensor based devices in many fields such as games, e-learning and medical image processing. While traditional human-computer interface devices such as the keyboard and mouse still dominate in our daily life, the existing work consists of less accuracy and some external devices are used to communicate between them. This work proposes a real time hand gesture recognition system for human computer interaction (HCI) this proposed work can recognize two different hand gestures at faster rate with reasonable accuracy. The gestures are classified on the basis of shape based features. Using hand as a device can help people communicate with computers in a more efficient way. This system consists of three main modules like hand segmentation, hand tracking, and gesture recognition from hand features. This feature work focuses the users get the ability to interact with the application from a distance without any physical interaction with keyboard or mouse. The proposed work allows users to track their fingers moving in three-dimensional space

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2023

This work presents a computer-vision-based application for recognizing hand gestures. A live video feed is captured by a camera, and a still image is extracted from that feed with the aid of an interface. At least once per count hand gesture (one, two, three, four, and five), the system is trained. After that, the system is given a test gesture to see if it can identify it. Several algorithms that are capable of distinguishing a hand gesture were studied. It was determined that the highest rate of accuracy was achieved by using the computational neural network known as the Alexnet algorithm. Traditionally, systems have used data gloves or markers as a means of input. We are free to use the system however we like. In this way, the user can make natural hand gestures in front of the camera. The system implemented serves as an extendable basis for future work toward a fully robust hand gesture recognition system, which is still the subject of intensive research and development.

IJRET

As our dependency on computers is increasing every day, these intelligent machines are making inroads in our daily life and society. This requires more friendly methods for interaction between humans and computers (HCI) than the conventionally used interaction devices (mouse & keyboard) because they are unnatural and cumbersome to use at times (by disabled people). Gesture Recognition can be useful under such conditions and provides intuitive interaction. Gestures are natural and intuitive means of communication and mostly occur from hands or face of human beings. This work introduces a hand gesture recognition system to recognize real time gestures of the user (finger movements) in unstrained environments. This is an effort to adapt computers to our natural means of communication: Speech and Hand Movements. All the work has been done using Matlab 2011b and in a real time environment which provides a robust technique for feature extraction and speech processing. A USB 2.0 camera continuously tracks the movement of user’s finger which is covered with red marker by filtering out green and blue colors from the RGB color space. Java based commands are used to implement the mouse movement through moving finger and GUI keyboard. Then a microphone is used to make use of the speech processing and instruct the system to click on a particular icon or folder throughout the screen of the system. So it is possible to take control of the whole computer system. Experimental results show that proposed method has high accuracy and outperforms Sub-gesture Modeling based methods

Sahib Singh & Vijay Kumar Banga , 2013

As our dependency on computers is increasing every day, these intelligent machines are making inroads in our daily life and society. This requires more friendly methods for interaction between humans and computers (HCI) than the conventionally used interaction devices (mouse & keyboard) because they are unnatural and cumbersome to use at times (by disabled people). Gesture Recognition can be useful under such conditions and provides easy, natural and intuitive interaction. Gestures are natural and intuitive means of communication and mostly occur from hands or face of human beings. This work introduces a hand gesture recognition system to recognize real time gestures of the user (finger movements) in unstrained environments. This is an effort to adapt computers to our natural means of communication: Speech and Hand Movements. In this work we have presented a technique for extracting the hand movement of the user and then through speech processing clicking a desired icon or folder or any other application of the computer system. All the work has been done using Matlab 2011b and in a real time environment which provides a robust technique for feature extraction and speech processing. A USB 2.0 camera continuously tracks the movement of user‟s finger which is covered with red marker by filtering out green and blue colors from the RGB color space. Java based commands are used to implement the mouse movement through moving finger and GUI keyboard. Then a microphone is used to make use of the speech processing and instruct the system to click on a particular icon or folder throughout the screen of the system. So it is possible to take control of the whole computer system. Experimental results show that proposed method has high accuracy and outperforms Sub-gesture Modeling based methods [6].