Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Object Recognition in Human Computer Interaction:- A Comparative Analysis

Kaushik Ranade, Tanmay Khule, Riddhi More

TL;DR

A comprehensive analysis of algorithms for face and gesture recognition in the context of computer vision and HCI is provided, with the goal of improving the design and development of interactive systems that are more intuitive, efficient, and user-friendly.

Abstract

Human-computer interaction (HCI) has been a widely researched area for many years, with continuous advancements in technology leading to the development of new techniques that change the way we interact with computers. With the recent advent of powerful computers, we recognize human actions and interact accordingly, thus revolutionizing the way we interact with computers. The purpose of this paper is to provide a comparative analysis of various algorithms used for recognizing user faces and gestures in the context of computer vision and HCI. This study aims to explore and evaluate the performance of different algorithms in terms of accuracy, robustness, and efficiency. This study aims to provide a comprehensive analysis of algorithms for face and gesture recognition in the context of computer vision and HCI, with the goal of improving the design and development of interactive systems that are more intuitive, efficient, and user-friendly.

Object Recognition in Human Computer Interaction:- A Comparative Analysis

TL;DR

A comprehensive analysis of algorithms for face and gesture recognition in the context of computer vision and HCI is provided, with the goal of improving the design and development of interactive systems that are more intuitive, efficient, and user-friendly.

Abstract

Human-computer interaction (HCI) has been a widely researched area for many years, with continuous advancements in technology leading to the development of new techniques that change the way we interact with computers. With the recent advent of powerful computers, we recognize human actions and interact accordingly, thus revolutionizing the way we interact with computers. The purpose of this paper is to provide a comparative analysis of various algorithms used for recognizing user faces and gestures in the context of computer vision and HCI. This study aims to explore and evaluate the performance of different algorithms in terms of accuracy, robustness, and efficiency. This study aims to provide a comprehensive analysis of algorithms for face and gesture recognition in the context of computer vision and HCI, with the goal of improving the design and development of interactive systems that are more intuitive, efficient, and user-friendly.

Paper Structure

This paper contains 12 sections, 3 figures, 1 table.

Table of Contents

  1. Introduction
  2. Methodology
  3. Algoirthms
  4. Dataset
  5. Face Recognition
  6. Gesture Recognition
  7. Review and Comparison of various Algorithms
  8. Face Recognition Algorithms
  9. Deep Learning-Based Techniques
  10. Conclusion
  11. Funding
  12. Competing Interests

Figures (3)

  • Figure 1: This image mediapipe shows the 21 hand landmarks that are detected by the MediaPipe Hand Landmark detection API. The landmarks, numbered and labeled in the image, are utilized to track the position and orientation of the hand in real-time.
  • Figure 2: This image illustrates the architecture of LSTM network
  • Figure 3: This image illustrates the Neural Network architecture used to predict the gestures.