세계의 컴퓨터 비전 시장 규모, 점유율, 성장 분석 : 컴포넌트별, 제품별, 최종 용도별 - 업계 예측(2023-2030년)
Global Computer Vision Market Size, Share, Growth Analysis, By Component(Hardware, Software), By Product(Smart Camera Based, PC-Based), By End-Use(Industrial, Non-industrial) - Industry Forecast 2023-2030
세계의 컴퓨터 비전 시장 규모는 2021년에 112억 2,000만 달러를 기록하고, 예측기간(2023-2030년) CAGR은 7%로, 2022년 120억 1,000만 달러에서 2030년에는 220억 7,000만 달러로 성장할 전망입니다.
딥러닝 알고리즘과 인공지능의 급속한 진보가 컴퓨터 비전 시장 성장에 크게 기여하고 있습니다. 이러한 기술에 의해 기계는 시각 데이터를 보다 정확하게 처리·해석할 수 있게 되고, 컴퓨터 비전 애플리케이션 성능 향상으로 이어지고 있습니다. 다양한 업계의 자동화와 로보틱스 수요는 컴퓨터 비전 기술 채용을 지지하고 있습니다.
세계의 컴퓨터 비전 시장에 대해 조사했으며, 시장 개요, 상부 시장 분석, 시장 역학과 전망, 각종 분석에 의한 시장 인사이트, 부문·지역별 시장 분석, 기업 개요 등의 정보를 제공합니다.
Computer Vision Market size was valued at USD 11.22 billion in 2021 and is poised to grow from USD 12.01 billion in 2022 to USD 22.07 billion by 2030, growing at a CAGR of 7% in the forecast period (2023-2030).
The global computer vision market refers to the industry that encompasses the development and deployment of computer vision technology and solutions. Computer vision involves the extraction, analysis, and interpretation of visual data from images or videos to enable machines to understand and interpret the visual world like humans. It encompasses various applications such as image recognition, object detection, facial recognition, gesture recognition, and video analysis.
Top-down and bottom-up approaches were used to estimate and validate the size of the Global computer vision Market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined by using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
Segments covered in this report:
The global computer vision market is segmented on the basis of component, product, end-use, and region. Based on the component, the Computer Vision Market is segmented into hardware and software. Based on the product, the market is segmented into SmartCamera based and PC-based. Based on the end-use, the Computer Vision Market is segmented into industrial and non-industrial. Whereas, based on region, the market is segmented into North America, Europe, Asia-Pacific, South America, and Middle East & Africa.
The rapid advancements in deep learning algorithms and artificial intelligence have significantly contributed to the growth of the computer vision market. These technologies enable machines to process and interpret visual data more accurately, leading to improved performance in computer vision applications. The demand for automation and robotics across various industries has fueled the adoption of computer vision technology. Computer vision systems are used to enable robots to perceive and interact with the environment, leading to increased efficiency, accuracy, and productivity in tasks such as object sorting, quality inspection, and autonomous navigation.
Implementing computer vision technology requires significant investment in hardware, software, and skilled personnel. Additionally, maintaining and upgrading the systems can incur additional costs. High upfront expenses can be a barrier for small and medium-sized enterprises (SMEs) and limit market growth.
The integration of computer vision with IoT devices is a growing trend. By combining computer vision capabilities with IoT sensors and devices, organizations can create intelligent systems for applications such as smart surveillance, predictive maintenance, and autonomous vehicles. As computer vision technology becomes more complex and sophisticated, there is a growing need for explainable AI. Explainable AI techniques aim to provide transparency and insights into the decision-making process of computer vision algorithms, enabling users to understand and trust the outcomes.