E-commerce Opens Up New Revenue Generation Avenue for Global Image Recognition Market
Image recognition solutions are revolutionising how businesses manage customer interfaces, market products both offline and online, and manage store inventories. The technology is playing a vital role in assisting manufacturers, marketers, and retailers in understanding their markets and react dynamically. In recent years, the image recognition technology is being used to search and buy products online.
A case in point is Snapchat's parent company, Snap, is currently working on developing a visual product feature in the application that will leverage features of image recognition technology to benefit customers by allowing them to take pictures of products in the real world and recognise, browse, and purchase products on Amazon.
The thriving e-commerce industry, especially due to the COVID-19 pandemic, has reframed the shopping experiences as traditional sales campaigns and marketing strategies and visual merchandising strategies have become obsolete. As a result, retailers are rapidly adapting to the new era of artificial intelligence (AI) and image recognition to provide next-generation customer experiences. The use of image recognition for product placement, shelf recognition, and merchandising standards is thus gaining traction.
Smoother Retail Experience with Cloud-powered Image Recognition Solutions Boost Market
Cloud providers such as Amazon Web Services (AWS), Microsoft, and Google are heavily investing in improving their image recognition market offerings in order to optimise in-store and online retail execution. The outbreak of COVID-19 has increased demand for cloud-based services even further. Intelligence Retail, a provider of computer vision and artificial intelligence (AI) for merchandising solutions, uses the IBM cloud and analytics solution with cutting-edge graphics processing unit (GPUs) to help businesses drive sales, reduce audit costs, boost performance, and drive customer loyalty.
Microsoft is trying to leverage its Microsoft Azure stack to process massive amounts of data quickly for store shelf management and to enable representatives to gain real-time visibility into the retail execution process. Trax partnered with Google Cloud in early 2019 to leverage Google Cloud's cloud and edge computing technology, coupled with Trax's image recognition and machine learning ability to efficiently control the in-store inventory and every SKU on the shelf with actionable real-time insights.
Salesforce, an American cloud-based CRM company, launched Consumer Goods Cloud in 2019 to improve the in-store experience through artificial intelligence. The Consumer Goods Cloud enables field representatives to ensure the optimal shelf stock levels while also providing an image recognition and object detection solution for easy inventory management and planogram compliance checks. Such organic and inorganic techniques, backed by underlying cloud infrastructure, would help the image recognition market grow in the future.
High Cost of Image Recognition Services Dissuade Small Businesses
The high cost of developing image recognition systems may be a barrier to market growth. The majority of enabling technologies, such as face recognition, deep learning, computer vision, AI, ML, and gesture recognition are extremely expensive to develop. As a result, even if they are interested in image recognition solutions to increase productivity, companies with limited financial resources do not pursue them.
Well-known vendor solutions in the market, such as Microsoft Computer Vision API, Microsoft Emotion API, Amazon Rekognition, Google Cloud Vision API, and IBM Watson Visual Recognition are expensive, making them difficult to deploy for small businesses. The high cost of implementing image recognition solutions and training AI enablers to perform a specific task will deter small retail and e-commerce businesses, and this may act as a restraint for image recognition solution vendors during the forecast period.
Acquisitions to Remain Integral to Business Expansion
In July 2019, Trax Image Recognition, a computer vision and analytics solution provider for retail acquired Planorama, the supplier of image recognition services. This acquisition helped Trax to add deep learning-based image recognition technology from Planorama to its existing features that include market measurement and analytics services powered by image recognition, machine learning, and IoT platforms.
The global image recognition AI camera market is fragmented owing to the presence of several companies that provides varied AI camera types. However, the companies that hold the majority share in the AI camera market are Samsung Electronics, Honeywell International, LG Electronics, Huawei Technology, HuddleCamHD, HikVision Sony Corporation, Xiaomi Inc, Google LLC, Apple Inc, Nikon Corporation, Fujitsu Ltd, and other prominent players.
Regional Classification of the Global Image Recognition AI Camera Market is Listed Below:
North America
Europe
Asia Pacific
Latin America
Middle East and Africa
*Regions and countries are subject to change based on data availability.
Key Elements Included In The Study: Global Image Recognition AI Camera Market
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1. Executive Summary
1.1. Global Image Recognition AI Camera Market: Snapshot
1.2. Future Projections, 2023 - 2030, (US$ Mn)
1.3. Key Segment Analysis and Competitive Insights
1.4. Premium Insights
2. Market Overview
2.1. Market Definitions and Segmentation
2.2. Market Dynamics
2.2.1. Driver
2.2.2. Restraint
2.2.3. Industry Challenges & Opportunities
2.3. Market Forces Analysis
2.3.1. Value Chain Analysis
2.3.2. Porters Five Forces Analysis
2.4. Challenges and Solutions
2.5. Supply Chain Impact Analysis
2.6. COVID-19 Impact Analysis
2.6.1. Pre and Post Covid-19 Analysis
2.7. Regulatory Scenario
2.8. Economic Analysis
3. Global Image Recognition AI Camera Market Outlook, 2019 - 2030
3.1. Global Image Recognition AI Camera Market Outlook, by Component, Value (US$ Mn), 2019 - 2030
3.1.1. Key Highlights
3.1.1.1. Software
3.1.1.2. Hardware
3.1.1.3. Services
3.1.2. Market Attractiveness Analysis
3.2. Global Image Recognition AI Camera Market Outlook, by Deployment, Value (US$ Mn), 2019 - 2030
3.2.1. Key Highlights
3.2.1.1. Cloud
3.2.1.2. On-premises
3.2.2. Market Attractiveness Analysis
3.3. Global Image Recognition AI Camera Market Outlook, by Technique, Value (US$ Mn), 2019 - 2030
3.3.1. Key Highlights
3.3.1.1. Face Recognition
3.3.1.2. Object Recognition
3.3.1.3. Barcode Recognition
3.3.1.4. Misc.
3.3.2. Market Attractiveness Analysis
3.4. Global Image Recognition AI Camera Market Outlook, by End-user, Value (US$ Mn), 2019 - 2030
3.4.1. Key Highlights
3.4.1.1. Banking, Finance services, and Insurance
3.4.1.2. Retail & E-commerce
3.4.1.3. Manufacturing
3.4.1.4. Agriculture
3.4.1.5. Healthcare
3.4.1.6. Media & Entertainment
3.4.1.7. Transportation
3.4.1.8. IT & Telecom
3.4.1.9. Misc. (Government, etc.)
3.4.2. Market Attractiveness Analysis
3.5. Global Image Recognition AI Camera Market Outlook, by Region, Value (US$ Mn), 2019 - 2030
3.5.1. Key Highlights
3.5.1.1. North America
3.5.1.2. Europe
3.5.1.3. Asia Pacific
3.5.1.4. Latin America
3.5.1.5. Middle East & Africa
3.5.2. Market Attractiveness Analysis
4. North America Image Recognition AI Camera Market Outlook, 2019 - 2030
4.1. North America Image Recognition AI Camera Market Outlook, by Component, Value (US$ Mn), 2019 - 2030
4.1.1. Key Highlights
4.1.1.1. Software
4.1.1.2. Hardware
4.1.1.3. Services
4.2. North America Image Recognition AI Camera Market Outlook, by Deployment, Value (US$ Mn), 2019 - 2030
4.2.1. Key Highlights
4.2.1.1. Cloud
4.2.1.2. On-premises
4.3. North America Image Recognition AI Camera Market Outlook, by Technique, Value (US$ Mn), 2019 - 2030
4.3.1. Key Highlights
4.3.1.1. Face Recognition
4.3.1.2. Object Recognition
4.3.1.3. Barcode Recognition
4.3.1.4. Misc.
4.4. North America Image Recognition AI Camera Market Outlook, by End-user, Value (US$ Mn), 2019 - 2030
4.4.1. Key Highlights
4.4.1.1. Banking, Finance services, and Insurance
4.4.1.2. Retail & E-commerce
4.4.1.3. Manufacturing
4.4.1.4. Agriculture
4.4.1.5. Healthcare
4.4.1.6. Media & Entertainment
4.4.1.7. Transportation
4.4.1.8. IT & Telecom
4.4.1.9. Misc. (Government, etc.)
4.5. North America Image Recognition AI Camera Market Outlook, by Country, Value (US$ Mn), 2019 - 2030
4.5.1. Key Highlights
4.5.1.1. U.S.
4.5.1.2. Canada
5. Europe Image Recognition AI Camera Market Outlook, 2019 - 2030
5.1. Europe Image Recognition AI Camera Market Outlook, by Component, Value (US$ Mn), 2019 - 2030
5.1.1. Key Highlights
5.1.1.1. Software
5.1.1.2. Hardware
5.1.1.3. Services
5.2. Europe Image Recognition AI Camera Market Outlook, by Deployment, Value (US$ Mn), 2019 - 2030
5.2.1. Key Highlights
5.2.1.1. Cloud
5.2.1.2. On-premises
5.3. Europe Image Recognition AI Camera Market Outlook, by Technique, Value (US$ Mn), 2019 - 2030
5.3.1. Key Highlights
5.3.1.1. Face Recognition
5.3.1.2. Object Recognition
5.3.1.3. Barcode Recognition
5.3.1.4. Misc.
5.4. Europe Image Recognition AI Camera Market Outlook, by End-user, Value (US$ Mn), 2019 - 2030
5.4.1. Key Highlights
5.4.1.1. Banking, Finance services, and Insurance
5.4.1.2. Retail & E-commerce
5.4.1.3. Manufacturing
5.4.1.4. Agriculture
5.4.1.5. Healthcare
5.4.1.6. Media & Entertainment
5.4.1.7. Transportation
5.4.1.8. IT & Telecom
5.4.1.9. Misc. (Government, etc.)
5.5. Europe Image Recognition AI Camera Market Outlook, by Country, Value (US$ Mn), 2019 - 2030
5.5.1. Key Highlights
5.5.1.1. Germany
5.5.1.2. France
5.5.1.3. U.K.
5.5.1.4. Norway
5.5.1.5. Turkey
5.5.1.6. Russia
5.5.1.7. Rest of Europe
5.5.2. BPS Analysis/Market Attractiveness Analysis
6. Asia Pacific Image Recognition AI Camera Market Outlook, 2019 - 2030
6.1. Asia Pacific Image Recognition AI Camera Market Outlook, by Component, Value (US$ Mn), 2019 - 2030
6.1.1. Key Highlights
6.1.1.1. Software
6.1.1.2. Hardware
6.1.1.3. Services
6.2. Asia Pacific Image Recognition AI Camera Market Outlook, by Deployment, Value (US$ Mn), 2019 - 2030
6.2.1. Key Highlights
6.2.1.1. Cloud
6.2.1.2. On-premises
6.3. Asia Pacific Image Recognition AI Camera Market Outlook, by Technique, Value (US$ Mn), 2019 - 2030
6.3.1. Key Highlights
6.3.1.1. Face Recognition
6.3.1.2. Object Recognition
6.3.1.3. Barcode Recognition
6.3.1.4. Misc.
6.4. Asia Pacific Image Recognition AI Camera Market Outlook, by End-user, Value (US$ Mn), 2019 - 2030
6.4.1. Key Highlights
6.4.1.1. Banking, Finance services, and Insurance
6.4.1.2. Retail & E-commerce
6.4.1.3. Manufacturing
6.4.1.4. Agriculture
6.4.1.5. Healthcare
6.4.1.6. Media & Entertainment
6.4.1.7. Transportation
6.4.1.8. IT & Telecom
6.4.1.9. Misc. (Government, etc.)
6.5. Asia Pacific Image Recognition AI Camera Market Outlook, by Country, Value (US$ Mn), 2019 - 2030
6.5.1. Key Highlights
6.5.1.1. China
6.5.1.2. Japan
6.5.1.3. South Korea
6.5.1.4. India
6.5.1.5. Singapore
6.5.1.6. Rest of Asia Pacific
6.5.2. BPS Analysis/Market Attractiveness Analysis
7. Latin America Image Recognition AI Camera Market Outlook, 2019 - 2030
7.1. Latin America Image Recognition AI Camera Market Outlook, by Component, Value (US$ Mn), 2019 - 2030
7.1.1. Key Highlights
7.1.1.1. Software
7.1.1.2. Hardware
7.1.1.3. Services
7.2. Latin America Image Recognition AI Camera Market Outlook, by Deployment, Value (US$ Mn), 2019 - 2030
7.2.1. Key Highlights
7.2.1.1. Cloud
7.2.1.2. On-premises
7.3. Latin America Image Recognition AI Camera Market Outlook, by Technique, Value (US$ Mn), 2019 - 2030
7.3.1. Key Highlights
7.3.1.1. Face Recognition
7.3.1.2. Object Recognition
7.3.1.3. Barcode Recognition
7.3.1.4. Misc.
7.4. Latin America Image Recognition AI Camera Market Outlook, by End-user, Value (US$ Mn), 2019 - 2030
7.4.1. Key Highlights
7.4.1.1. Banking, Finance services, and Insurance
7.4.1.2. Retail & E-commerce
7.4.1.3. Manufacturing
7.4.1.4. Agriculture
7.4.1.5. Healthcare
7.4.1.6. Media & Entertainment
7.4.1.7. Transportation
7.4.1.8. IT & Telecom
7.4.1.9. Misc. (Government, etc.)
7.5. Latin America Image Recognition AI Camera Market Outlook, by Country, Value (US$ Mn), 2019 - 2030
7.5.1. Key Highlights
7.5.1.1. Brazil
7.5.1.2. Mexico
7.5.1.3. Rest of Latin America
7.5.2. BPS Analysis/Market Attractiveness Analysis
8. Middle East & Africa Image Recognition AI Camera Market Outlook, 2019 - 2030
8.1. Middle East & Africa Image Recognition AI Camera Market Outlook, by Component, Value (US$ Mn), 2019 - 2030
8.1.1. Key Highlights
8.1.1.1. Software
8.1.1.2. Hardware
8.1.1.3. Services
8.2. Middle East & Africa Image Recognition AI Camera Market Outlook, by Deployment, Value (US$ Mn), 2019 - 2030
8.2.1. Key Highlights
8.2.1.1. Cloud
8.2.1.2. On-premises
8.3. Middle East & Africa Image Recognition AI Camera Market Outlook, by Technique, Value (US$ Mn), 2019 - 2030
8.3.1. Key Highlights
8.3.1.1. Face Recognition
8.3.1.2. Object Recognition
8.3.1.3. Barcode Recognition
8.3.1.4. Misc.
8.4. Middle East & Africa Image Recognition AI Camera Market Outlook, by End-user, Value (US$ Mn), 2019 - 2030
8.4.1. Key Highlights
8.4.1.1. Banking, Finance services, and Insurance
8.4.1.2. Retail & E-commerce
8.4.1.3. Manufacturing
8.4.1.4. Agriculture
8.4.1.5. Healthcare
8.4.1.6. Media & Entertainment
8.4.1.7. Transportation
8.4.1.8. IT & Telecom
8.4.1.9. Misc. (Government, etc.)
8.5. Middle East & Africa Image Recognition AI Camera Market Outlook, by Country, Value (US$ Mn), 2019 - 2030
8.5.1. Key Highlights
8.5.1.1. GCC
8.5.1.2. South Africa
8.5.1.3. Rest of Middle East & Africa
8.5.2. BPS Analysis/Market Attractiveness Analysis
9. Competitive Landscape
9.1. Company Market Share Analysis, 2022
9.2. Competition Matrix (By Tier and Size of companies)
9.3. Strategic Collaborations
9.3.1. Joint Ventures
9.3.2. Mergers & Acquisitions
9.4. Company Profiles
9.4.1. Amazon Web Services, Inc.
9.4.1.1. Company Overview
9.4.1.2. Product Portfolio
9.4.1.3. Financial Overview
9.4.1.4. Business Strategies and Development
(*Note: Above details would be available for below list of companies based on availability)
9.4.2. Clarifai, Inc.
9.4.3. Google LLC
9.4.4. IBM Corporation
9.4.5. Intel Corporation
9.4.6. Micron Technology, Inc.
9.4.7. Microsoft Corporation
9.4.8. NVIDIA Corporation
9.4.9. Qualcomm Technologies, Inc.
9.4.10. Samsung Electronics Co., Ltd.
9.4.11. Xilinx Inc.
10. Appendix
10.1. Acronyms and Abbreviations
10.2. Research Scope & Assumptions
10.3. Research Methodology and Information Sources
Considering the volatility of business today, traditional approaches to strategizing a game plan can be unfruitful if not detrimental. True ambiguity is no way to determine a forecast. A myriad of predetermined factors must be accounted for such as the degree of risk involved, the magnitude of circumstances, as well as conditions or consequences that are not known or unpredictable. To circumvent binary views that cast uncertainty, the application of market research intelligence to strategically posture, move, and enable actionable outcomes is necessary.
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