Global Video Analytics Growth Opportunities

Global Video Analytics Growth Opportunities

Maturing Facial Recognition and Emotion Intelligence Capabilities Accelerate Future Growth Potential

RELEASE DATE
01-Sep-2021
REGION
Global
Research Code: PBEC-01-00-00-00
SKU: IT04379-GL-MT_25737
$2,450.00
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Description

Historical and real-time enterprise video is growing rapidly. While the data can create immense value for organizations, the large data volume makes it impossible for humans to process the data. A near-real-time analysis is necessary to make effective decisions and take actions, creating high dependence on enabling technologies, including video analytics.

The COVID-19 pandemic also drives businesses to recognize video’s value and increase technology investments to access insights and achieve business outcomes. While the pandemic has led governments and organizations worldwide to adopt facial recognition technologies, video analytics needs a holistic approach in device management, solutions, infrastructure, and data security to derive maximum value.

As artificial intelligence (AI) capabilities mature amid the rise of machine learning, deep learning, availability of edge infrastructure, and application programming interface (API) integration, video analytics capabilities are registering a usage surge. Video analytics adoption is growing in various sectors and industries, with face recognition at the core and enabling more accuracy. Vendors augment facial recognition with detection and analytical capabilities to classify and analyze facial expressions and human emotions. Combining digital technologies, behavioral science, and psychology allows enterprises to leverage emotional intelligence to gain strategic advantage. Thus, video analytics is finding new use cases, with emotion AI vital in driving its adoption.

The increasing video analytics applications offer significant opportunities to software and hardware vendors and service providers. Monetizing emerging opportunities necessitates revisiting and reshaping business models to fit current needs. Given the nascent stage and high potential of emerging technologies such as emotion AI, stakeholders must create niche industry use case-driven strategy and identify ways to encourage initial adoption.

Author: Nishchal Khorana

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Table of Contents

Why is it Increasingly Difficult to Grow?

The Strategic Imperative 8™

The Impact of the Top Three Strategic Imperatives on the Video Analytics Market

Growth Opportunities Fuel the Growth Pipeline Engine™

Growth Environment

Growth Environment (continued)

Enterprise Video Analytics Value Chain

Enterprise Video Analytics Value Chain (continued)

Enterprise Video Analytics Value Chain (continued)

Facial Recognition

Facial Recognition (continued)

Facial Recognition (continued)

Facial Recognition (continued)

Emotion AI

Emotion AI (continued)

Emotion AI (continued)

Emotion AI (continued)

Emotion AI (continued)

Emotion AI (continued)

The Way Forward

The Way Forward (continued)

The Way Forward (continued)

The Way Forward (continued)

Company to Watch—EnableX

Company to Watch—Deeplite

Growth Opportunity 1: Industry Vertical/Function-specific Applications to Enhance Customer Value

Growth Opportunity 1: Industry Vertical/Function-specific Applications to Enhance Customer Value (continued)

Growth Opportunity 2: As-a-Service Model for Emotion Analytics Solutions to Accelerate Adoption

Growth Opportunity 2: As-a-Service Model for Emotion Analytics Solutions to Accelerate Adoption (continued)

Growth Opportunity 3: Edge Infrastructure Enabling Video Analytics Deployment

Growth Opportunity 3: Edge Infrastructure Enabling Video Analytics Deployment (continued)

List of Exhibits

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Related Research
Historical and real-time enterprise video is growing rapidly. While the data can create immense value for organizations, the large data volume makes it impossible for humans to process the data. A near-real-time analysis is necessary to make effective decisions and take actions, creating high dependence on enabling technologies, including video analytics. The COVID-19 pandemic also drives businesses to recognize videos value and increase technology investments to access insights and achieve business outcomes. While the pandemic has led governments and organizations worldwide to adopt facial recognition technologies, video analytics needs a holistic approach in device management, solutions, infrastructure, and data security to derive maximum value. As artificial intelligence (AI) capabilities mature amid the rise of machine learning, deep learning, availability of edge infrastructure, and application programming interface (API) integration, video analytics capabilities are registering a usage surge. Video analytics adoption is growing in various sectors and industries, with face recognition at the core and enabling more accuracy. Vendors augment facial recognition with detection and analytical capabilities to classify and analyze facial expressions and human emotions. Combining digital technologies, behavioral science, and psychology allows enterprises to leverage emotional intelligence to gain strategic advantage. Thus, video analytics is finding new use cases, with emotion AI vital in driving its adoption. The increasing video analytics applications offer significant opportunities to software and hardware vendors and service providers. Monetizing emerging opportunities necessitates revisiting and reshaping business models to fit current needs. Given the nascent stage and high potential of emerging technologies such as emotion AI, stakeholders must create niche industry use case-driven strategy and identify ways to encourage initial adoption. Author: Nishchal Khorana
More Information
No Index No
Podcast No
Author Nishchal Khorana
Industries Information Technology
WIP Number PBEC-01-00-00-00
Is Prebook No
GPS Codes 9523-D1,9705-C1,9658