Hand Gesture Recognition Is a More Advanced Task Requiring Separating the Hand Region From an Image, Which Can Be Used in VR Games and Sign Languages

EasyChair Preprint no. 12517

Abstract

Hand gesture recognition is an increasingly sophisticated task with various applications, including virtual reality (VR) games and sign languages. This abstract explores the challengesand techniques involved in separating the hand region from an image for accurate hand gesturerecognition. Recognizing hand gestures involves identifying and interpreting the movements and configurations of the hand and fingers. One of the initial steps in this process is isolating thehand region from the rest of the image. This separation task presents unique challenges due tovariations in hand appearance, complex backgrounds, and occlusions. To address these challenges, researchers have developed various techniques for hand regionsegmentation. These techniques typically involve a combination of image processing andmachine learning algorithms. Image processing techniques may include background subtraction, skin color-based segmentation, or hand shape modeling. Machine learning approaches, suchasconvolutional neural networks (CNNs) or random forests, can also be employed to learn handappearance patterns and classify hand vs. non-hand regions.

Keyphrases: computer, reality, virtual

@Booklet{EasyChair:12517,
  author = {Favour Olaoye and Kaledio Potter},
  title = {Hand Gesture Recognition Is a More Advanced Task Requiring Separating the Hand Region From an Image, Which Can Be Used in VR Games and Sign Languages},
  howpublished = {EasyChair Preprint no. 12517},

  year = {EasyChair, 2024}}