scholarly journals Implementation and Performance Analysis of Different Hand Gesture Recognition Methods

2019 ◽  
pp. 13-20
Author(s):  
Md. Manik Ahmed ◽  
Md. Anwar Hossain ◽  
A F M Zainul Abadin
Keyword(s):  
Computer Vision ◽  
Human Computer Interaction ◽  
Gesture Recognition ◽  
Optimization Technique ◽  
Light Condition ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Model Accuracy ◽  
Recognition Model ◽  
Computer Interaction

In recent few years, hand gesture recognition is one of the advanced grooming technologies in the era of human computer interaction and computer vision due to a wide area of application in the real world. But it is a very complicated task to recognize hand gesture easily due to gesture orientation, light condition, complex background, translation and scaling of gesture images. To remove this limitation, several research works have developed which is successfully decrease this complexity. However, the intention of this paper is proposed and compared four different hand gesture recognition system and apply some optimization technique on it which ridiculously increased the existing model accuracy and model running time. After employed the optimization tricks, the adjusted gesture recognition model accuracy was 93.21% and the run time was 224 seconds which was 2.14% and 248 seconds faster than an existing similar hand gesture recognition model. The overall achievement of this paper could be applied for smart home control, camera control, robot control, medical system, natural talk, and many other fields in computer vision and human-computer interaction.

scholarly journals Efficient Gesture based Language Recognition using SVM and Lloyd’s Algorithm

2019 ◽  
Vol 8 (2S3) ◽  
pp. 927-930
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Computer Vision ◽  
Human Computer Interaction ◽  
Gesture Recognition ◽  
Hand Gesture Recognition ◽  
Video Data ◽  
Hand Gesture ◽  
Language Recognition ◽  
Computer Interaction

undertaking in the field of human-computer interaction (HCI) and computer vision. 10 years prior to the undertaking appeared to be practically unsolvable with the data given by a single RGB camera. In this work, we have actualized a presumable exact strategy to perceive static gestures or image frames from a live camera or video data. As Hand Gesture Recognition is identified with two noteworthy fields of image processing and AI (machine learning), in this way, this report likewise refers to the different tools and APIs that can be utilized to implement different strategies and methods in these fields

scholarly journals To Control Electrical MCBs using Hand Gesture Recognition

2015 ◽  
Vol 14 (9) ◽  
pp. 6102-6106
Author(s):  
Sangeeta Goyal ◽  
Dr. Bhupesh Kumar
Keyword(s):  
Human Computer Interaction ◽  
Gesture Recognition ◽  
Human Body ◽  
Circuit Breaker ◽  
Hand Gesture Recognition ◽  
Hand Movements ◽  
Hand Gesture ◽  
Handicapped Person ◽  
New Techniques ◽  
Computer Interaction

There has been growing interest in development of new techniques and methods for Human-Computer Interaction (HCI). Gesture Recognition is one of the important areas of this technology. Gesture Recognition means interfacing with computer using motion of human body typically hand movements. As a Handicapped person cannot move very easily and quickly if there is a fire in house or he/she cannot switch off the Miniature Circuit Breaker (MCB) but the same task can be done easily with hand gesture recognition. In our proposed system electrical MCB can be controlled using hand gesture recognizer. To switch on/off the MCB, we need to provide hand based gesture as an input to system.

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