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1374874

全球情绪侦测与识别市场 - 2023-2030

Global Emotion Detection And Recognition Market - 2023-2030

出版日期: 2023年11月01日 | 出版商:

DataM Intelligence | 英文 201 Pages | 商品交期: 约2个工作天内

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简介目录

概述

全球情绪侦测与辨识市场在 2022 年达到 222 亿美元，预计到 2030 年将达到 444 亿美元，2023-2030 年预测期间复合年增长率为 11.4%。

全球情绪检测和识别市场的推动是由于健康、行销、零售和安全等各个领域的需求增加。情绪检测有多种方法用于分析资料和解释情绪。电脑视觉演算法主要用于影像处理和情感检测。

对情绪检测和识别 (EDR) 的需求主要是由人工智慧和机器学习的不断增长的使用所推动的。 EDR 模型使用 AI 和 ML 演算法进行训练，以从一系列资料来源（包括语音、生理讯号和脸部表情）中识别和识别情绪。具有人工智慧和机器学习功能的 EDR 系统比传统的 EDR 系统更精确。

这是因为人工智慧和机器学习演算法能够识别人们难以看到的资料中的复杂模式。人工智慧和机器学习技术越先进，人工智慧和机器学习驱动的 EDR 解决方案就越便宜。因此，现在更广泛的组织和企业可以更容易使用它。

亚太地区是情绪侦测和识别市场成长最快的地区，占整个市场的近2/5。亚太地区是世界上最大、扩张最快的医疗保健市场之一。医疗保健产业正在使用 EDR 技术来增强病患照护和治疗效果。

例如，EDR 系统可用于追踪和识别患者的情绪，这使医疗专业人员能够更好地了解患者的需求并提供更个人化的治疗。该地区的各种研究人员正在投资开发先进技术，为市场创造机会。

动力学

广泛应用于情绪侦测和识别的感测器

面部表情和肢体语言是使用视觉感测器（包括摄影机）记录的。辨识情绪最关键的指标之一是脸部表情，它可以传达多种感受，包括快乐、悲伤、愤怒和恐惧。眼神交流、姿势和手势是肢体语言的例子，可以提供有关情绪状态的重要细节。

语音和其他发声由音讯感测器（包括麦克风）录製。言语是辨识情绪的有用工具，包括恐惧、愤怒、悲伤和享受。笑声和泪水是发声的例子，可以提供有关一个人情绪状况的资讯。

检测和识别情绪的技术有许多可能的用途。它可用于创造新颖的医疗方法、客製化行销工作和增强客户服务。此外，它还可用于提供全新的教学和娱乐体验。监测心臟电活动的非侵入性测试的一个例子是心电图 (EKG)。它用于各种心臟疾病的诊断和监测。

行销和广告需求不断增长

情绪检测和识别市场的技术进步为公司提供了有关消费者情绪的宝贵见解。在娱乐领域，这些技术可以帮助公司了解客户的偏好。因此，采用这些技术的需求增加。它有助于从消费者那里获取信息，这些信息随后用于市场增长。

线上平台对其产品进行市场篮分析。它们决定了消费者的搜寻模式。借助该演算法，公司或品牌可以针对特定领域的特定受众。透过应用关联规则，他们将产品与其买家联繫起来。透过识别消费者的心理状态，行销人员瞄准了他们的受众。

隐私和安全问题

捕捉个人影像的情绪侦测和识别会导致隐私问题。它技术分析个人和敏感资料，例如表情和生理过程。它引发了人们对资料和隐私外洩的安全性的担忧，因为骇客行为增加了人们对与任何人工智慧工具共享个人资料的担忧。

使用者接受度和信任也是情绪侦测和辨识系统需求下降的一个主要因素。企业需要对用户资料更加谨慎。将情绪侦测应用程式整合到其他技术中是一项复杂的任务。因为与其他软体会有相容性问题。

The global emotion detection and recognition market is driven due to increases in demand for various sectors such as the health, marketing, retail and security sectors. Emotions detection has various methods used to analyze the data and interpret emotions. Computer vision algorithms are majorly used for image processing and emotion detection.

The demand for emotion detection and recognition (EDR) is mostly driven by the growing use of AI and ML. EDR models are trained using AI and ML algorithms to identify and identify emotions from a range of data sources, including speech, physiological signals and facial expressions. EDR systems with AI and ML capabilities are more precise than conventional EDR systems.

It is due to the fact that AI and ML algorithms have the ability to recognize intricate patterns in data that are hard for people to see. The more advanced AI and ML technologies get, the less expensive AI and ML-powered EDR solutions get. It are now more reachable by a wider range of organizations and businesses as a result.

Asia-Pacific is the fastest-growing region in the emotion detection and recognition market covering nearly 2/5th of the total market. One of the largest and most rapidly expanding healthcare marketplaces in the world can be found in Asia-Pacific. The healthcare sector is using EDR technologies to enhance patient care and results.

EDR systems, for instance, may be used to track and identify patients' emotions, which enables medical professionals to better understand their patients' requirements and deliver more individualized treatment. Various researchers in the region are investing in developing advanced technology leading to creating opportunities for the market.

Dynamics

Sensors Widely Used in Emotion Detection and Recognition

Facial expressions and body language are recorded using visual sensors, including cameras. One of the most crucial indicators for identifying emotions is facial expressions, which can convey a variety of feelings including joy, sorrow, rage and fear. Eye contact, posture and gestures are examples of body language that can provide important details about emotional state.

Speech and other vocalizations are recorded by audio sensors, including microphones. Speech is a useful tool for identifying emotions including fear, rage, sadness and enjoyment. Laughter and tears are examples of vocalizations that might provide information about one's emotional condition.

Technologies for detecting and identifying emotions have many possible uses. It may be applied to create novel medical treatments, tailor marketing efforts and enhance customer service. Additionally, it may be utilized to provide brand-new instructional and entertaining experiences. An example of a noninvasive test that monitors the electrical activity of the heart is the Electrocardiogram (EKG). It is employed in the diagnosis and monitoring for various cardiac diseases.

Rising Demand in Marketing and Advertising

The advancement in technology in the emotion detection and recognition market in which it provides valuable insights to companies about consumer emotions. In the entertainment sector, these technologies help companies to understand customer preferences. Due to this, the demand for adoption of these technologies increases. It helps to gain information from consumers which is later used for market growth.

Online platforms use market-basket analysis on their product. In which they determine the search pattern of the consumer. With the help of this algorithm companies or brands target a particular audience in a specific domain. By applying the association rule they relate the product and its buyer. By identifying the consumer's state of mind marketer targets their audience.

Privacy and Security Concerns

Emotion detection and recognition which capture images of individual persons lead to privacy concerns. It technology analyzes personal and sensitive data such as expressions and physiological processes. It raises concerns about the security of breaches of data and privacy, as hacking increases people are worried about sharing their personal data with any AI tools.

User acceptance and trust is also a major factor due to which demand for emotion detection and recognition system decreases. Companies need to be more cautious about user data. Integrating emotion detection applications into other technology is a complex task. As there will be compatibility issues with other software.

Segment Analysis

The global emotion detection and recognition are segmented based on technology, application, end-user and region.

Technological Advancements In Facial Recognition

With the rapid growth of facial recognition, it has been used in many industries. It works on facial segmentation of images which detects the emotions of any individual. There are various AI detection models that detect emotions. The emotions detection system works on many different parameters such as eye activity, motion analysis and skin resistance measurements. The technology has gained immense popularity in developed countries like U.S. and Canada due to the rising adoption of advanced technology thus covering more than 34.9% in the region.

The detection of emotion depends upon the local features of the face. For example, if the emotion detection tools detect the person's emotions such as anger or sadness, these factors can lead to detecting physiological responses such as there might be increased heart rate or any other issues. Emotional intelligence plays a major role in the detection and recognition of the decision-making process for individuals.

Companies have invested heavily in the market leading to a boost the segmental revenue. For instance, in October 2019, Fujitsu Laboratories, Ltd. and Fujitsu Laboratories of America, Inc. has announced the development of artificial intelligence (AI) face expression recognition technology that accurately recognizes small changes in facial expression. The new technique was created in partnership with the School of Computer Science at Carnegie Mellon University.

Geographical Penetration

North America: Leading the Growth of Emotion Detection And Recognition Market

In North America, AI and ML technologies are becoming more and more popular, especially in the EDR market. It is a result of the region's expanding computing power and data availability. North American governments are encouraging the development and implementation of EDR technology increasingly. It is a result of governments realizing how EDR technology may boost the efficacy and efficiency of public services. Because multimodal EDR systems are more accurate and less expensive than traditional EDR solutions, they are growing in popularity in North America.

EDR is being utilized in the healthcare sector to identify and track individuals who suffer from anxiety and depression. Additionally, EDR can assist patients in regulating their stress and provide better pain management. EDR is used in education to determine whether students are struggling and to evaluate student participation. EDR can be employed to the development of customized educational initiatives. EDR is being employed in the workplace to raise productivity and employee happiness. Workplace violence may also be identified and prevented with the use of EDR. Future EDR applications will likely offer up even more ground-breaking and innovative concepts as the technology develops.

Competitive Landscape

The major global players in the market include: Kairos AR, Inc., iMotions A/S, Noldus Information Technology BV, Amazon.com, Inc., Realeyes, IBM Corporation, Google LLC, Emotibot Technologies Limited, NuraLogix Corporation, Entropik Technologies Pvt . Ltd.

COVID-19 Impact Analysis

Globally, the pandemic has had a major negative influence on mental health, leading to higher levels of emotional discomfort, worry and stress. Technologies that detect emotions have been used to track and evaluate mental health issues. The significance of these tools in remotely monitoring and treating mental health concerns has been further highlighted by the pandemic

Systems for identifying and monitoring emotions that heavily rely on facial expressions have faced challenges as a result of the COVID-19 pandemic. Due to this masks are frequently used during social interactions as a precaution against the spread of the illness. So was challenging to recognize faces since the mask was leading to a loss of information.

Russia-Ukraine Conflict Analysis

In both accuracy and conclusions, emotion recognition algorithms often need a lot of different types of training data. The Ukraine conflict might restrict information-gathering efforts and have a consequence on the quantity and variety of data used to train emotion recognition algorithms. The growth of emotion detection technology in the area may be limited if data collection attempts are affected by the war.

The regional market dynamics, particularly the market for emotion detection, may be affected by the war. The demand as well as the growth in emotion detection technology in the affected regions, notably Russia and Ukraine, may be impacted by instability, economic difficulties and political uncertainty related to the conflict. Modifications in market growth and investment may result from this.

AI Analysis

AI-powered emotion detection systems may be trained on a variety of datasets, which enables them to fully understand and identify emotions in a wide range of linguistic, socioeconomic and demographic situations. The flexibility and functionality of emotion detection systems in various market segments and industries are facilitated by their ability to adapt and extend.

AI algorithms are built to quickly digest data, allowing instantaneous emotion recognition and detection. It capacity is especially useful in situations requiring fast input or a reaction based on emotions, such as video analysis, virtual meetings or live customer encounters. Real-time data analysis capabilities of emotion detection systems powered by AI allow for rapid insights and adaptive reactions. It advanced feature of emotion detection and recognition system has increased its demand in the market. Making it a solution for both online and offline modes, considering the situation during the COVID-19 pandemic.

By Technology

Machine Learning
Natural Language Processing
Pattern Recognition Network
Others

By Application

Facial Recognition
Speech and Voice Recognition
Bio-sensing
Others

By End-User

Government
Healthcare
Retail
Entertainment
E-learning
Others

By Region

North America
- U.S.
- Canada
- Mexico
Europe
- Germany
- UK
- France
- Italy
- Spain
- Rest of Europe
South America
- Brazil
- Argentina
- Rest of South America
Asia-Pacific
- China
- India
- Japan
- Australia
- Rest of Asia-Pacific
Middle East and Africa

Key Developments

For instance on 5 July 2022, Zoom announced 'ZoomIQ' which detect human emotions and facial expression. It technology can be used by salespeople so they can pitch their sales according to the emotions of individuals.
For instance on 7 Jun 2023, kouo launches a platform that is powered by AI which is used for emotions analytics.

Why Purchase the Report?

To visualize the global emotion detection and recognition market segmentation based on technology, application, end-user and region, as well as understand key commercial assets and players.
Identify commercial opportunities by analyzing trends and co-development.
Excel data sheet with numerous data points of battery collapsible PV systems market-level with all segments.
PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
End-User mapping available as Excel consisting of key End-Users of all the major players.

The global emotion detection and recognition market report would provide approximately 61 tables, 62 figures and 201 Pages.

Target Audience 2023

Manufacturers/ Buyers
Industry Investors/Investment Bankers
Research Professionals
Emerging Companies

1. Methodology and Scope

1.1. Research Methodology
1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

3.1. Snippet By Technology
3.2. Snippet By Application
3.3. Snippet By End-User
3.4. Snippet by Region

4. Dynamics

4.1. Impacting Factors
- 4.1.1. Drivers
  - 4.1.1.1. Sensors Widely Used in Emotion Detection and Recognition
  - 4.1.1.2. Rising Demand in Marketing and Advertising
- 4.1.2. Restraints
  - 4.1.2.1. Privacy and User Acceptance in the Emotion Detection and Recognition Market
- 4.1.3. Opportunity
- 4.1.4. Impact Analysis

5. Industry Analysis

5.1. Porter's Five Force Analysis
5.2. Supply Chain Analysis
5.3. Pricing Analysis
5.4. Regulatory Analysis
5.5. Russia-Ukraine War Impact Analysis
5.6. DMI Opinion

6. COVID-19 Analysis

6.1. Analysis of COVID-19
- 6.1.1. Scenario Before COVID
- 6.1.2. Scenario During COVID
- 6.1.3. Scenario Post COVID
6.2. Pricing Dynamics Amid COVID-19
6.3. Demand-Supply Spectrum
6.4. Government Initiatives Related to the Market During Pandemic
6.5. Manufacturers' Strategic Initiatives
6.6. Conclusion

7. By Technology

7.1. Introduction
- 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 7.1.2. Market Attractiveness Index, By Technology
7.2. Machine Learning*
- 7.2.1. Introduction
- 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
7.3. Natural Language Processing
7.4. Pattern Recognition Network
7.5. Others

8. By Application

8.1. Introduction
- 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 8.1.2. Market Attractiveness Index, By Application
8.2. Facial Recognition*
- 8.2.1. Introduction
- 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
8.3. Speech and Voice Recognition

9. By End-User

9.1. Introduction
- 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 9.1.2. Market Attractiveness Index, By End-User
9.2. Government*
- 9.2.1. Introduction
- 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
9.3. Healthcare
9.4. Retail
9.5. Amorphous Silicon

10. By Region

10.1. Introduction
- 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
- 10.1.2. Market Attractiveness Index, By Region
10.2. North America
- 10.2.1. Introduction
- 10.2.2. Key Region-Specific Dynamics
- 10.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 10.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 10.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 10.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 10.2.6.1. U.S.
  - 10.2.6.2. Canada
  - 10.2.6.3. Mexico
10.3. Europe
- 10.3.1. Introduction
- 10.3.2. Key Region-Specific Dynamics
- 10.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 10.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 10.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 10.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 10.3.6.1. Germany
  - 10.3.6.2. UK
  - 10.3.6.3. France
  - 10.3.6.4. Italy
  - 10.3.6.5. Spain
  - 10.3.6.6. Rest of Europe
10.4. South America
- 10.4.1. Introduction
- 10.4.2. Key Region-Specific Dynamics
- 10.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 10.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 10.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 10.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 10.4.6.1. Brazil
  - 10.4.6.2. Argentina
  - 10.4.6.3. Rest of South America
10.5. Asia-Pacific
- 10.5.1. Introduction
- 10.5.2. Key Region-Specific Dynamics
- 10.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 10.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 10.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 10.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 10.5.6.1. China
  - 10.5.6.2. India
  - 10.5.6.3. Japan
  - 10.5.6.4. Australia
  - 10.5.6.5. Rest of Asia-Pacific
10.6. Middle East and Africa
- 10.6.1. Introduction
- 10.6.2. Key Region-Specific Dynamics
- 10.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 10.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 10.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User

11. Competitive Landscape

11.1. Competitive Scenario
11.2. Market Positioning/Share Analysis
11.3. Mergers and Acquisitions Analysis

12. Company Profiles

12.1. Kairos AR,Inc.*
- 12.1.1. Company Overview
- 12.1.2. Product Portfolio and Description
- 12.1.3. Financial Overview
- 12.1.4. Key Developments
12.2. iMotions A/S
12.3. Nodules Information Technology BV
12.4. Amazon.com,Inc
12.5. Realeyes
12.6. IBM Corporation
12.7. Google LLC
12.8. Koppers Inc.
12.9. Noldus Information Technology BV
12.10. Entropik Technologies Pvt. Ltd.

LIST NOT EXHAUSTIVE

13. Appendix

13.1. About Us and Services
13.2. Contact Us

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