얼굴 인식 시장 : 유형별, 컴퓨팅별, 산업별, 용도별 - 세계 예측(2025-2030년)

The Face Recognition Market was valued at USD 7.64 billion in 2023, expected to reach USD 9.28 billion in 2024, and is projected to grow at a CAGR of 21.83%, to USD 30.46 billion by 2030.

The scope of the face recognition market is expanding significantly due to its increasing application across various sectors such as security, retail, healthcare, and automotive. Face recognition technology uses biometric software applications capable of uniquely identifying or verifying a person by comparing and analyzing facial contours. Its necessity arises from the growing need for enhanced security systems, the rising demand for surveillance systems across various industries, and the integration of biometrics in smartphones, emphasizing convenience and user authentication. The application scope extends to border control, crime prevention, access control, and personalized marketing in retail. End-use sectors are increasingly diverse, with significant growth expectations in government, BFSI (Banking, Financial Services, and Insurance), healthcare, and consumer electronics. Key factors driving market growth include advances in AI and machine learning, increased government initiatives for facial recognition systems' deployment, and rapid technological advancements in mobile devices. Current market opportunities lie in the integration of face recognition in cloud computing and the development of emotion detection capabilities, which can enhance customer experience in retail and hospitality industries. However, the market faces challenges such as privacy concerns, data protection issues, and regulatory constraints, especially in regions with strict data privacy laws. Additionally, the high-cost implications of implementing advanced recognition systems can hinder smaller enterprises. Innovation potential exists in improving accuracy and speed of recognition systems through stronger algorithms and AI integration, enhancing security features to prevent spoofing, and developing more user-friendly systems to broaden market appeal. For business growth, companies should focus on diversification of application areas, partnerships with tech companies for AI improvements, and adopting strategies that emphasize data security and user consent. The market is projected to evolve dynamically, driven by technological trends and regulatory landscape shifts.

Market Dynamics: Unveiling Key Market Insights in the Rapidly Evolving Face Recognition Market

The Face Recognition Market is undergoing transformative changes driven by a dynamic interplay of supply and demand factors. Understanding these evolving market dynamics prepares business organizations to make informed investment decisions, refine strategic decisions, and seize new opportunities. By gaining a comprehensive view of these trends, business organizations can mitigate various risks across political, geographic, technical, social, and economic domains while also gaining a clearer understanding of consumer behavior and its impact on manufacturing costs and purchasing trends.

• Market Drivers
  • Increased Cyber-Attacks and Identity Theft Necessitating the Incorporation of Better Security Systems
  • Increasing Demand for Surveillance Systems to Enhance Safety and Security
  • Adoption of AI Integrated Biometric Face Recognition Technology
• Market Restraints
  • Lack of Accuracy and High Cost of Implementation
  • Complicated Storage and Maintenance of Updated Data
• Market Opportunities
  • Increasing Growth Potential with Government Initiatives
  • Increasing Adoption of Facial Recognition in Consumer Electronics
• Market Challenges
  • Concerns Associated with Individual Data Privacy and Loosely Defined Regulatory Framework

Porter's Five Forces: A Strategic Tool for Navigating the Face Recognition Market

Porter's five forces framework is a critical tool for understanding the competitive landscape of the Face Recognition Market. It offers business organizations with a clear methodology for evaluating their competitive positioning and exploring strategic opportunities. This framework helps businesses assess the power dynamics within the market and determine the profitability of new ventures. With these insights, business organizations can leverage their strengths, address weaknesses, and avoid potential challenges, ensuring a more resilient market positioning.

PESTLE Analysis: Navigating External Influences in the Face Recognition Market

External macro-environmental factors play a pivotal role in shaping the performance dynamics of the Face Recognition Market. Political, Economic, Social, Technological, Legal, and Environmental factors analysis provides the necessary information to navigate these influences. By examining PESTLE factors, businesses can better understand potential risks and opportunities. This analysis enables business organizations to anticipate changes in regulations, consumer preferences, and economic trends, ensuring they are prepared to make proactive, forward-thinking decisions.

Market Share Analysis: Understanding the Competitive Landscape in the Face Recognition Market

A detailed market share analysis in the Face Recognition Market provides a comprehensive assessment of vendors' performance. Companies can identify their competitive positioning by comparing key metrics, including revenue, customer base, and growth rates. This analysis highlights market concentration, fragmentation, and trends in consolidation, offering vendors the insights required to make strategic decisions that enhance their position in an increasingly competitive landscape.

FPNV Positioning Matrix: Evaluating Vendors' Performance in the Face Recognition Market

The Forefront, Pathfinder, Niche, Vital (FPNV) Positioning Matrix is a critical tool for evaluating vendors within the Face Recognition Market. This matrix enables business organizations to make well-informed decisions that align with their goals by assessing vendors based on their business strategy and product satisfaction. The four quadrants provide a clear and precise segmentation of vendors, helping users identify the right partners and solutions that best fit their strategic objectives.

Key Company Profiles

The report delves into recent significant developments in the Face Recognition Market, highlighting leading vendors and their innovative profiles. These include Neurotechnology, FaceFirst, Inc., Cognitec Systems GmbH, Shanghai Yitu Technology Co., Ltd., Zoloz Co., Ltd., Fujitsu Limited, IDEMIA, Amazon Web Services, Inc., Clarifai, Inc., FacePhi SDK, Clearview AI, Inc., id3 Technologies, Daon, Inc., AnyVision Interactive Technologies Ltd., NEC Corporation, Microsoft Corporation, Visage Technologies d.o.o., Megvii by Beijing Kuangshi Technology Co., Ltd., Panasonic Corporation, Innovatrics, s.r.o., Ayonix Corporation, NVISO SA, Hangzhou Hikvision Digital Technology Co., Ltd., and Thales Group.

Market Segmentation & Coverage

This research report categorizes the Face Recognition Market to forecast the revenues and analyze trends in each of the following sub-markets:

• Based on Type, market is studied across Artificial Neural Networks, Classical Face Recognition Algorithms, D-based Face Recognition, Face Descriptor-based Methods, and Video-based Recognition.
• Based on Computing, market is studied across Cloud Computing and Edge Computing.
• Based on Vertical, market is studied across Automotive & Transportation, BFSI, Consumer Goods & Retail, Education, Energy & Utilities, Government & Defense, Healthcare, Manufacturing, and Telecommunications & IT.
• Based on Application, market is studied across Access Control, Advertising, Attendance Tracking & Monitoring, eLearning, Emotion Recognition, Law Enforcement, Payment, and Robotics.
• Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

The report offers a comprehensive analysis of the market, covering key focus areas:

1. Market Penetration: A detailed review of the current market environment, including extensive data from top industry players, evaluating their market reach and overall influence.

2. Market Development: Identifies growth opportunities in emerging markets and assesses expansion potential in established sectors, providing a strategic roadmap for future growth.

3. Market Diversification: Analyzes recent product launches, untapped geographic regions, major industry advancements, and strategic investments reshaping the market.

4. Competitive Assessment & Intelligence: Provides a thorough analysis of the competitive landscape, examining market share, business strategies, product portfolios, certifications, regulatory approvals, patent trends, and technological advancements of key players.

5. Product Development & Innovation: Highlights cutting-edge technologies, R&D activities, and product innovations expected to drive future market growth.

The report also answers critical questions to aid stakeholders in making informed decisions:

1. What is the current market size, and what is the forecasted growth?

2. Which products, segments, and regions offer the best investment opportunities?

3. What are the key technology trends and regulatory influences shaping the market?

4. How do leading vendors rank in terms of market share and competitive positioning?

5. What revenue sources and strategic opportunities drive vendors' market entry or exit strategies?

Table of Contents

1. Preface

• 1.1. Objectives of the Study
• 1.2. Market Segmentation & Coverage
• 1.3. Years Considered for the Study
• 1.4. Currency & Pricing
• 1.5. Language
• 1.6. Stakeholders

2. Research Methodology

• 2.1. Define: Research Objective
• 2.2. Determine: Research Design
• 2.3. Prepare: Research Instrument
• 2.4. Collect: Data Source
• 2.5. Analyze: Data Interpretation
• 2.6. Formulate: Data Verification
• 2.7. Publish: Research Report
• 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

• 5.1. Market Dynamics
  • 5.1.1. Drivers
    • 5.1.1.1. Increased Cyber-Attacks and Identity Theft Necessitating the Incorporation of Better Security Systems
    • 5.1.1.2. Increasing Demand for Surveillance Systems to Enhance Safety and Security
    • 5.1.1.3. Adoption of AI Integrated Biometric Face Recognition Technology
  • 5.1.2. Restraints
    • 5.1.2.1. Lack of Accuracy and High Cost of Implementation
    • 5.1.2.2. Complicated Storage and Maintenance of Updated Data
  • 5.1.3. Opportunities
    • 5.1.3.1. Increasing Growth Potential with Government Initiatives
    • 5.1.3.2. Increasing Adoption of Facial Recognition in Consumer Electronics
  • 5.1.4. Challenges
    • 5.1.4.1. Concerns Associated with Individual Data Privacy and Loosely Defined Regulatory Framework
• 5.2. Market Segmentation Analysis
  • 5.2.1. Type: Increasing preference of 3D-based face recognition for virtual reality applications
  • 5.2.2. Computing: Centralized cloud computing approach offering data processing and storage for face recognition applications
  • 5.2.3. Vertical: Broad scope in business verticals for enhanced security and personalized user experience
  • 5.2.4. Application: Diverse applications for access control and emotion recognition
• 5.3. Porter's Five Forces Analysis
  • 5.3.1. Threat of New Entrants
  • 5.3.2. Threat of Substitutes
  • 5.3.3. Bargaining Power of Customers
  • 5.3.4. Bargaining Power of Suppliers
  • 5.3.5. Industry Rivalry
• 5.4. PESTLE Analysis
  • 5.4.1. Political
  • 5.4.2. Economic
  • 5.4.3. Social
  • 5.4.4. Technological
  • 5.4.5. Legal
  • 5.4.6. Environmental
• 5.5. Client Customization
  • 5.5.1. Necessary Steps to Adhere to General Data Protection Regulation (GDPR)

6. Face Recognition Market, by Type

• 6.1. Introduction
• 6.2. Artificial Neural Networks
• 6.3. Classical Face Recognition Algorithms
• 6.4. D-based Face Recognition
• 6.5. Face Descriptor-based Methods
• 6.6. Video-based Recognition

7. Face Recognition Market, by Computing

• 7.1. Introduction
• 7.2. Cloud Computing
• 7.3. Edge Computing

8. Face Recognition Market, by Vertical

• 8.1. Introduction
• 8.2. Automotive & Transportation
• 8.3. BFSI
• 8.4. Consumer Goods & Retail
• 8.5. Education
• 8.6. Energy & Utilities
• 8.7. Government & Defense
• 8.8. Healthcare
• 8.9. Manufacturing
• 8.10. Telecommunications & IT

9. Face Recognition Market, by Application

• 9.1. Introduction
• 9.2. Access Control
• 9.3. Advertising
• 9.4. Attendance Tracking & Monitoring
• 9.5. eLearning
• 9.6. Emotion Recognition
• 9.7. Law Enforcement
• 9.8. Payment
• 9.9. Robotics

10. Americas Face Recognition Market

• 10.1. Introduction
• 10.2. Argentina
• 10.3. Brazil
• 10.4. Canada
• 10.5. Mexico
• 10.6. United States

11. Asia-Pacific Face Recognition Market

• 11.1. Introduction
• 11.2. Australia
• 11.3. China
• 11.4. India
• 11.5. Indonesia
• 11.6. Japan
• 11.7. Malaysia
• 11.8. Philippines
• 11.9. Singapore
• 11.10. South Korea
• 11.11. Taiwan
• 11.12. Thailand
• 11.13. Vietnam

12. Europe, Middle East & Africa Face Recognition Market

• 12.1. Introduction
• 12.2. Denmark
• 12.3. Egypt
• 12.4. Finland
• 12.5. France
• 12.6. Germany
• 12.7. Israel
• 12.8. Italy
• 12.9. Netherlands
• 12.10. Nigeria
• 12.11. Norway
• 12.12. Poland
• 12.13. Qatar
• 12.14. Russia
• 12.15. Saudi Arabia
• 12.16. South Africa
• 12.17. Spain
• 12.18. Sweden
• 12.19. Switzerland
• 12.20. Turkey
• 12.21. United Arab Emirates
• 12.22. United Kingdom

13. Competitive Landscape

• 13.1. Market Share Analysis, 2023
• 13.2. FPNV Positioning Matrix, 2023
• 13.3. Competitive Scenario Analysis
  • 13.3.1. Intellicene Adds Oosto Facial Recognition Technology To Symphia Product Suite
  • 13.3.2. BigBear.ai to Acquire Pangiam, Combining Facial Recognition and Advanced Biometrics with BigBear.ai's Computer Vision Capabilities to Spearhead the Vision AI Industry
  • 13.3.3. Telpo Launches Self-Checkout Terminal With Facial Recognition Option

Companies Mentioned

• 1. Neurotechnology
• 2. FaceFirst, Inc.
• 3. Cognitec Systems GmbH
• 4. Shanghai Yitu Technology Co., Ltd.
• 5. Zoloz Co., Ltd.
• 6. Fujitsu Limited
• 7. IDEMIA
• 8. Amazon Web Services, Inc.
• 9. Clarifai, Inc.
• 10. FacePhi SDK
• 11. Clearview AI, Inc.
• 12. id3 Technologies
• 13. Daon, Inc.
• 14. AnyVision Interactive Technologies Ltd.
• 15. NEC Corporation
• 16. Microsoft Corporation
• 17. Visage Technologies d.o.o.
• 18. Megvii by Beijing Kuangshi Technology Co., Ltd.
• 19. Panasonic Corporation
• 20. Innovatrics, s.r.o.
• 21. Ayonix Corporation
• 22. NVISO SA
• 23. Hangzhou Hikvision Digital Technology Co., Ltd.
• 24. Thales Group