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pose estimation market Report Overview
The global pose estimation market size was USD 77.19 million in 2021 and is expected to reach USD 143.58 million by 2027, exhibiting a CAGR of 10.9% during the forecast period. The COVID-19 pandemic has been unprecedented and staggering, with pose estimation experiencing lower-than-anticipated demand across all regions compared to pre-pandemic levels. The sudden rise in CAGR is attributable to the market’s growth and demand returning to pre-pandemic levels.
Pose estimation is a computer vision technique used to determine the spatial position and orientation of objects or entities within an image or video. It plays a crucial role in various applications, including robotics, augmented reality, gesture recognition, and human-computer interaction. The primary goal of pose estimation is to extract information about the pose of objects or individuals, typically represented as their 2D or 3D position and orientation in space. There are two main types of pose estimation: 2D pose estimation and 3D pose estimation. In 2D pose estimation, the objective is to determine the position and orientation of objects or body parts within a 2D image or video frame. This is often used in applications like facial landmark detection, where the goal is to locate key points on a person's face. In contrast, 3D pose estimation aims to estimate the 3D position and orientation of objects or entities within a 3D space, which is crucial for tasks like robotic navigation and augmented reality. Pose estimation algorithms typically rely on techniques such as key point detection, feature matching, and machine learning, using data from sensors like cameras or depth sensors to make accurate pose estimations.
The market, prior to the global pandemic, was on a trajectory of rapid growth. This technology, which is crucial in computer vision applications, had gained immense traction across various industries such as healthcare, gaming, sports analytics, and robotics. The market was characterized by an increasing demand for accurate and real-time pose estimation solutions. However, the outbreak of COVID-19 disrupted economies and supply chains globally, impacting the market significantly.
COVID-19 Impact: Lockdown Posed Restrictions on Industries like Sports and Entertainment Hampering the Market Growth
The COVID-19 pandemic brought about several challenges for the pose estimation market. The initial phase of the pandemic resulted in supply chain disruptions, leading to delays in manufacturing and deployment of pose estimation systems. With lockdowns and restrictions in place, industries like sports and entertainment that heavily rely on pose estimation technologies witnessed a downturn. The uncertainty in the economic environment led to reduced investments in research and development, which impacted the market's growth.
Latest Trends
"Real-time Pose Estimation to Boost the Market Development."
Despite the challenges posed by the pandemic, a prominent trend in the market has been the increasing emphasis on real-time pose estimation. Real-time pose estimation refers to the ability of systems to track and analyze the position and movement of objects or individuals in real-time, often with minimal latency. This trend has gained momentum due to its applications in various sectors, including augmented reality (AR), virtual reality (VR), gaming, and autonomous robotics.
pose estimation market Segmentation
- By Type Analysis
According to type, the market can be segmented into 2D, 3D. 2D being the leading segment of the market by type analysis.
- By Application Analysis
Based on application, the market can be divided into Commercial, Research Institute, Personal Use. Commercial being the leading segment of the market by application analysis.
Driving Factors
"Advancements in AI and Machine Learning to Drive the Market Growth"
One of the key drivers propelling the market's growth is the continuous advancements in artificial intelligence (AI) and machine learning (ML) algorithms. AI and ML have played a pivotal role in improving the accuracy and robustness of pose estimation systems. These technologies have enabled pose estimation systems to handle complex scenarios and variations in real-world conditions, making them more reliable and efficient. With the development of deep learning models and neural networks, pose estimation algorithms have become capable of handling multiple keypoints simultaneously, even in cluttered or occluded environments. This has opened up new opportunities for applications in fields like autonomous vehicles, where accurate real-time pose estimation is critical for safe navigation. This has in return helped in increasing the pose estimation market growth.
"Expanding Application in Healthcare to Drive the Market Development"
The healthcare industry has emerged as a significant driver for the market, increasing its market share. Pose estimation technology has found applications in areas such as physical therapy, biomechanics, and patient monitoring. In physical therapy, for instance, it is used to assess and guide patients through exercises, ensuring they perform movements correctly to aid in recovery. In biomechanics research, pose estimation is instrumental in understanding human and animal movements, contributing to advancements in prosthetics and orthopedics. Furthermore, the COVID-19 pandemic accelerated the adoption of telemedicine and remote monitoring solutions, and pose estimation played a vital role in enabling remote physical therapy and patient assessment. These trends have expanded the pose estimation market share within the healthcare sector.
Restraining Factors
"Privacy and Ethical Concerns to Impede the Market Growth"
As pose estimation systems become more sophisticated, they can capture detailed information about individuals' movements and postures. This data can be sensitive, leading to concerns about surveillance and misuse. Privacy regulations, such as the General Data Protection Regulation (GDPR) in Europe, have placed stringent requirements on the collection and use of personal data, including biometric data. Complying with these regulations adds complexity and costs to pose estimation system deployment. Moreover, ethical considerations related to consent, data ownership, and potential biases in the algorithms pose challenges for the market.
pose estimation market Regional Insights
"North America to Bolster the Market Share owing to Strong Presence of Technology Companies "
North America has been a prominent player in the market, consistently increasing its market share. The region's dominance can be attributed to several factors, including a strong presence of technology companies, substantial investments in research and development, and a diverse range of applications. In the United States, for example, the entertainment and gaming industry has been a significant adopter of pose estimation technology for motion capture in video games and animation. Additionally, North American companies have been at the forefront of developing AI and ML algorithms for pose estimation, contributing to the market's growth. Furthermore, the healthcare sector in North America has been quick to adopt pose estimation solutions for applications such as physical therapy and remote patient monitoring. The region's well-established healthcare infrastructure and willingness to embrace innovative technologies have fueled market expansion.
Key Industry Players
"Key Players Focus on Partnerships to Gain a Competitive Advantage "
Prominent market players are making collaborative efforts by partnering with other companies to stay ahead of the competition. Many companies are also investing in new product launches to expand their product portfolio. Mergers and acquisitions are also among the key strategies used by players to expand their product portfolios.
LIST OF TOP POSE ESTIMATION COMPANIES
- Xyonix (U.S.)
- Hacarus (Japan)
- Wrnch (Canada)
- BeyondMinds (Israel)
- Always AI (U.S.)
- Fritz AI (U.S.)
- IBM (U.S.)
- GlobalWalkers (South Korea)
- Google (U.S.)
- Microsoft (U.S.)
- Morpho (France)
Report Coverage
This research profiles a report with extensive studies that take into description the firms that exist in the market affecting the forecasting period. With detailed studies done, it also offers a comprehensive analysis by inspecting the factors like segmentation, opportunities, industrial developments, trends, growth, size, share, and restraints. This analysis is subject to alteration if the key players and probable analysis of market dynamics change.
REPORT COVERAGE | DETAILS |
---|---|
Market Size Value In |
US$ 77.19 Million in 2021 |
Market Size Value By |
US$ 143.58 Million by 2027 |
Growth Rate |
CAGR of 10.9% from 2021 to 2027 |
Forecast Period |
2022-2027 |
Base Year |
2023 |
Historical Data Available |
Yes |
Regional Scope |
Global |
Segments Covered |
Type and Application |
Frequently Asked Questions
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What value is the pose estimation market expected to touch by 2027?
The global pose estimation market is expected to reach USD 143.58 million by 2027.
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What CAGR is the pose estimation market expected to exhibit by 2027?
The pose estimation market is expected to exhibit a CAGR of 10.9% by 2027.
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Which are the driving factors of the pose estimation market?
Advancements in AI and machine learning and expanding application in healthcare are the driving factors of the pose estimation market.
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Which are the key players or most dominating companies functioning in the pose estimation market?
The dominating companies in the pose estimation market are Xyonix, Hacarus, Wrnch, BeyondMinds and Always AI.