Harnessing Emerging Business Opportunities Through Visual Intelligence
27-Dec-2017
Global
Technology Research
D7F5-01-00-00-00
IT03571-GL-TR_21365
Computer vision is a rapidly burgeoning field, with the potential to revolutionize various applications such as advanced driver assistance systems, medical imaging, precision agriculture, retail, advertising, media, security and surveillance, unmanned aerial vehicles (UAVs), and robotics.
This report answers the following questions:
• Which are the analytics sub-technologies that are being adopted?
• What are the major application areas for these technologies?
• What are some industries impacted?
• What are some use-cases of successful implementation?
• What are some innovative business models being driven by advanced analytics?
• What is the patent scenario globally?
• What are some game-changing convergence scenarios of advanced analytics with other disruptive technologies?
• What are the key findings of the analysis and analyst POV of the future?
Some of the computer vision sub-technologies covered are:
Image Recognition and analysis
Gesture Recognition
Facial Recognition
Motion Detection and Object Tracking
Eye Tracking
Emotion Recognition
1.1 Research Scope
2.1 Driving Systems, Medical Diagnostics, and Retail Will be Transformed by Intelligent Vision Systems
2.2 Gesture and Facial Recognition Will Revolutionize The Future of Customer Experience
2.3 Data: The Currency of the Future
3.1 What is Computer Vision and How is it Useful?
3.2 Some Significant Computer Vision Application Areas
3.3 Convolutional Neural Nets (CNNs) Have Spurred the Evolution of Computer Vision
3.4 Factors Driving the Adoption of Computer Vision
3.5 Factors Challenging the Adoption of Computer Vision
3.6 Advanced Analytics Technology Value Chain
3.7 Value From Intelligent Vision Systems
4.1 Computer Vision in Image Processing & Analytics
4.2 Which Companies are Enabling Image Analytics?
4.3 Why Computer Vision in Medicine?
4.4 Image Recognition Enables Automation in Healthcare – Use Case
4.5 Image Recognition Enables Hyper-personalization in Retail – Use Case
4.6 Image Recognition Enables Autotagging in Retail Leading to Greatly Automated Workflows– Use Case
4.7 Computer Vision Helps Marketers Measure “Share of Eye”
4.8 In-Image Advertising Helps Yeast Engagement Rise – Use Case
4.9 Computer Vision in Precision Agriculture Increases Efficiencies– Use Case
4.10 Computer Vision in Gesture Recognition
4.11 Which Companies are Enabling Gesture Recognition?
4.12 Gesture Recognition Increases Patient Engagement – Use Case
4.13 Gesture Recognition Enables an Enhanced User Experience (Ux) – Use Case
4.14 Computer Vision in Facial Recognition
4.15 Which Companies are Enabling Facial Recognition?
4.16 Facial Recognition Technology Enables Intelligent Attendance Systems – Use Case
4.17 Computer Vision in Motion Detection & Object Tracking
4.18 Which Companies are Enabling Object Detection & Tracking?
4.19 The Retail Store of the Future is Here Now – Use Case
4.20 ATM Surveillance With Uncanny Insights – Use Case
4.21 Real Time Alerts Enable Timely Action– Use Case (Continued)
4.22 Computer Vision in Eye Tracking Systems
4.23 Which Companies are Enabling Eye Tracking?
4.24 Eye Tracking in the Automotive Industry Leads to Hyper-personalization – Use Case
4.25 Computer Vision in Emotion Analytics
4.26 Which Companies are Enabling Emotion AI?
4.27 Emotion AI in Media and Advertising
4.28 Emotion AI in Gaming and Education
4.29 Emotion AI in Automotive and Robotics
4.30 Emotion Analytics is Increasingly Used in Autism Research– Use Case
4.31 Computer Vision in Automated Driver Assistance Systems (ADAS)
4.32 Which Companies are Enabling Computer Vision in ADAS?
4.33 Robotic Taxi Service a Reality– Use Case
5.1 Rise in Data and Computing Power Will Spur Innovation
5.2 Microsoft is Using the Cloud to Harness the Potential of AI
5.3 Computer Vision: Future Innovation Potential
6.1 Computer Vision: Key Funding Deals
6.2 Computer Vision: Mergers and Acquisitions
6.2 Computer Vision: Mergers and Acquisitions (Continued)
7.1 Convergence of Computer Vision, Deep Learning, and Biomarkers Will Lead to Prevention and Personalized Cures for Cancer
7.2 The Future of Retail Will Involve Hyper-personalization Delivered to Your Doorstep
7.3 Robots Will Use Computer Vision to Create Truly Intelligent Beings
7.4 Emerging Business Models – Technology Licensing is Spurring Innovation
7.5 Emerging Business Models – Crowdsourced Mobile Intelligence
8.1 Key Contacts
8.1 Key Contacts (continued)
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| Deliverable Type | Technology Research |
|---|---|
| No Index | No |
| Podcast | No |
| Author | Priya Sharma |
| Industries | Information Technology |
| WIP Number | D7F5-01-00-00-00 |
| Is Prebook | No |
| Ti Codes | 298300687,9A37-C1,9B07-C1,D900,D903,D905,D906,D907,D908,D90B,D90C,D90D,D910,D911,D912,D913,D915,D916,D91A,D91C,D920,D931,D932,D933,D935,D936,D937,D941,D944 |
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