Hand Gesture Recognition and Volume Control

: A systems that can recognize a hand motion in real time video is hand gesture recognition. Hand gestures are categorized according to their subject matter. The design of hand gesture recognition is one of the more difficult jobs, as it combines two significant issues. The detection of the hand is the first step and creating a sign that can only be utilized by one hand at a time. It can be used in a variety of settings, including human-computer interaction and sign language. The basic concept of hand segmentation and the hand detection system, which use the Haar-cascade classifier, may be used to construct hand gesture recognition using Python and OpenCV. This paper discuss a way for hand gesture identification based on shape-based features detection. The configuration comprises a single camera that captures the user's gesture and feeds it into the system. A fundamental goal of gesture recognition is to develop a system that can recognize specific human gestures and utilize them to send information for device control. With real-time gesture recognition, a user can operate a computer by making a specific gesture in front of a computer's camera. With the help of the OpenCV module, we will create a hand gesture. Without the use of a keyboard or mouse, the system can be controlled via hand gestures.

• Publication year

  2025

• Venue

  Social Science Research Network

• Publication date

  Unknown publication date

• Fields of study

  Not labeled

• Identifiers
  DOI 10.2139/ssrn.5161769
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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