Open Access
Neha Shrotriya,
Tripti Agrawal,
Tripti Somani,
Tanu Agrawal,
Yatika Bochiwal,
- Assistant Professor, Poornima College of Engineering, Jaipur, Rajasthan, India
- Student, Poornima College of Engineering, Jaipur, Rajasthan, India
- Student, Poornima College of Engineering, Jaipur, Rajasthan, India
- Student, Poornima College of Engineering, Jaipur, Rajasthan, India
- Student, Poornima College of Engineering, Jaipur, Rajasthan, India
Abstract
We explore the development of picture categorization methods in this paper, with an emphasis on how they are used to manipulate media players with hand gestures. Our investigation focuses on the development of machine learning techniques, particularly on supporting vector machines (SVM) and convolutional neural networks (CNN). SVMs are used to identify and authenticate people from digital photos or video clips, but CNNs are great at face detection, which is a key feature of gesture-based media player control systems. Our study examines several feature extraction techniques, with a focus on the efficiency of Histogram-Oriented Gradient for global feature representation. Furthermore, we go over the foundations of computer vision and emphasize how important they are for creating user-friendly interfaces for image processing and computer vision applications, particularly in the area of hand gesture-based media player control. various processing layer computer models can learn from and represent data with various levels of abstraction simulating thanks to deep learning. how the brain interprets and processes multimodal data, inadvertently capturing complex large-scale data structures. Neural networks, hierarchical probabilistic models, and other supervised and unsupervised feature learning algorithms are all part of the extensive family of techniques known as deep learning. The amount of complex data from various sources (e.g., visual, auditory, medical, social, and sensor) and the fact that deep learning approaches have been demonstrated to outperform prior state-of-the-art techniques in several tasks are the reasons behind the recent rise in interest in these techniques.
Keywords: Hand Recognition, Hand Movement, Video Control, Gestures, SVM, CNN, HOG, Biometric Authentication, computer vision.
[This article belongs to Recent Trends in Electronics Communication Systems(rtecs)]
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Recent Trends in Electronics Communication Systems
| Volume | 11 |
| Issue | 02 |
| Received | June 10, 2024 |
| Accepted | July 8, 2024 |
| Published | August 14, 2024 |