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Computer Vision - Thematic Intelligence

Publisher GlobalData
Published Oct 19, 2022
Length 83 Pages
SKU # GBDT17531759

Description

Computer Vision - Thematic Intelligence

Summary

The explosion in the volume of visual data, coupled with the increased sophistication of artificial neural networks and the availability of chips created specifically for artificial intelligence (AI) processes, will all drive growth in computer vision (CV) over the coming years. CV will find myriad applications in several industries, reaching a market size of $32.8 billion by 2030, up from $12.5 billion in 2021, according to GlobalData forecasts.

Key Highlights
  • The level of underlying intelligence required for CV in autonomous vehicles (AVs) and autonomous mobile robots (AMRs) is significantly higher than that needed to recognize faces or read barcodes. An internal three-dimensional representation of the world, spatial awareness, and planning and reasoning capabilities are needed. Fully autonomous vehicles (Level 5) are not expected until 2035, largely because of these CV challenges. Competition in these fields will intensify in the coming years.
  • Driven by ethical and political reasons, using CV in facial recognition will increase divergence over standards and regulatory approaches. This will ultimately lead to a supply chain decoupling in the CV segment, as is already underway in semiconductors. Once the regulatory wheels are in motion, it will likely impact the CV market beyond just facial recognition.
  • CV solutions rely on advanced AI chips due to the exponential increase in data sets’ sizes and algorithms’ complexity. As such, the ongoing US-China trade dispute, which has led to the US prohibiting exports to China of either advanced AI chips or the advanced tools to manufacture them, will disrupt the competitive landscape of the CV industry. As with AI chips and other advanced semiconductors, China will lose its CV market dominance unless it can secure access to advanced chip manufacturing technology.
Scope
  • This report provides an overview of the computer vision theme.
  • It identifies the key trends impacting growth of the theme over the next 12 to 24 months, split into three categories: technology trends, macroeconomic trends, and regulatory trends.
  • It includes global market forecasts for the computer vision market and analysis of patents, company filings, and hiring trends.
  • It contains details of M&A deals driven by the computer vision theme, and a timeline highlighting milestones in the development of computer vision.
  • The detailed value chain consists of three segment: hardware, software, and delivery.
Reasons to Buy
  • Computer vision is being commercialized across several areas, including automotive, consumer, industrial, medical, and entertainment.
  • This report provides a clear and concise analysis of computer vision, including valuable insights into how it works, what it is being used for, and which companies are at the forefront of its development. It also evaluates the controversial nature of technology like facial recognition and looks at how regulators could limit its use.

Table of Contents

83 Pages
  • Executive Summary
    • Figure 1: Who are the leading players in the computer vision theme, and where do they sit in the value chain?
    • What is computer vision?
    • Four key CV technologies
    • CV and ethics
    • Technology trends
    • Macroeconomic trends
    • Regulatory trends
    • Market size and growth forecasts
    • Competitive analysis
    • Use cases
    • Mergers and acquisitions
    • Patent trends
    • Company filings trends
    • Hiring trends
    • Timeline
    • Figure 29: The computer vision value chain
    • Hardware
    • Software
    • Delivery
    • Public companies
    • Private companies
    • Application software sector scorecard
    • Semiconductor sector scorecard
    • Consumer electronics sector scorecard
    • Glossary
    • GlobalData reports
    • Figure 56: Our five-step approach for generating a sector scorecard
  • About GlobalData
  • Contact Us

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