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Face Recognition Patent Deployment Strategies of Major IT Brands

  • ID: 4858737
  • Report
  • 29 Pages
  • Market Intelligence & Consulting Institute (MIC)
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FEATURED COMPANIES

  • Adobe Systems
  • Canon
  • Facebook
  • Google
  • IBM
  • Microsoft
  • MORE

Face recognition combines knowledge and techniques in biology, psychology, pattern recognition, image processing, image analysis, machine vision, AI (Artificial Intelligence), and can be widely used in a broad range of application scenarios such as home security, access control, driving monitoring, face payment, ATM, e-commerce, human-computer interaction, medical diagnosis, and identity verification. In recent years, it has attracted several international brands such as Microsoft, Amazon, IBM, Google, Intel, Apple, Facebook, Sony, and Samsung to invest in face recognition technology solutions and develop relevant applications. This report outlines key areas of face recognition patents granted by the USPTO (The United States Patent and Trademark Office) and examines patent deployment strategies of 20 major IT brands that focus on face recognition technology.

List of Topics:

  • Background of face recognition technology
  • Analysis of face recognition patent counts by field, by technology, by application for the period 2014-2018
  • Analysis of face recognition patent deployment strategies of 20 major IT brands, including Facebook, HP, Qualcomm, Panasonic, Adobe Systems, LG, Apple, DigitalOptics, Honeywell, Fujifilm, Eastman Kodak, Amazon, Intel, Canon, IBM, Samsung, Sony, Google, Microsoft, and FotoNation and includes the assessment of their R&D intensity.
Note: Product cover images may vary from those shown
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FEATURED COMPANIES

  • Adobe Systems
  • Canon
  • Facebook
  • Google
  • IBM
  • Microsoft
  • MORE

1. Technology Background
1.1 Definition

2. Patent Portfolio Deployment
2.1 Patent Mining
2.1 Patent Analysis
2.1.1 Analysis by Field
2.1.2 Analysis of Change in Patent Count Share by Field
2.1.3 Analysis by Field by Application Year
2.1.4 Analysis by Field by Brand
2.1.5 Analysis by Technology
2.1.6 Analysis by Technology and Application Year
2.1.7 Analysis by Technology by Brand
2.1.8 Analysis by Application
2.1.9 Analysis by Application by Application Year
2.1.10 Analysis of 20 Major IT Brands R&D Intensity

3. Author's Perspective

Appendix
Glossary of Terms
List of Companies

List of Tables
Table 1 Analysis of Change in the US Face Recognition Patent Count Share by Field, 2014-2018
Table 2 Analysis of US Face Recognition Patent Counts by Field by Application Year
Table 3 20 Major IT Brands and Their Face Recognition Patent Counts by Field
Table 4 US Face Recognition Patent Count Share by Technology
Table 5 Analysis of US Face Recognition Patent Counts by Technology by Application Year
Table 6 20 Major IT Brands and Their US Face Recognition Patent Counts by Technology
Table 7 US Face Recognition Patent Count Share by Application
Table 8 US Face Recognition Patent Counts by Application by Application Year

List of Figures
Figure 1 US Face Recognition Patent Count Share by Field
Figure 2 20 Major IT Brands and Their R&D Intensity Associated with Face Recognition Technology

Note: Product cover images may vary from those shown
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  • Adobe Systems
  • Amazon Technologies
  • Apple
  • Canon
  • DigitalOptics
  • Eastman Kodak
  • Facebook
  • FotoNation
  • Fujifilm
  • Google
  • Hewlett-Packard
  • Honeywell
  • IBM
  • Intel
  • LG
  • Microsoft
  • Panasonic
  • Qualcomm
  • Samsung
  • Sony
Note: Product cover images may vary from those shown
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Primary research with a holistic, cross-domain approach

The exhaustive primary research methods are central to the value that the analyst delivers. A combination of questionnaires and on-site visits to the major manufacturers provides a first view of the latest data and trends. Information is subsequently validated by interviews with the manufacturers' suppliers and customers, covering a holistic industry value chain. This process is backed up by a cross-domain team-based approach, creating an interlaced network across numerous interrelated components and system-level devices to ensure statistical integrity and provide in-depth insight.

Complementing primary research is a running database and secondary research of industry and market information. Dedicated research into the macro-environmental trends shaping the ICT industry also allows the analyst to forecast future development trends and generate foresight perspectives. With more than 20 years of experience and endeavors in research, the methods and methodologies include:

Method

  • Component supplier interviews
  • System supplier interviews
  • User interviews
  • Channel interviews
  • IPO interviews
  • Focus groups
  • Consumer surveys
  • Production databases
  • Financial data
  • Custom databases

Methodology

  • Technology forecasting and assessment
  • Product assessment and selection
  • Product life cycles
  • Added value analysis
  • Market trends
  • Scenario analysis
  • Competitor analysis

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