![]() |
市場調査レポート
商品コード
1715312
コンピュータビジョンにおける人工知能市場:コンポーネント、技術、機能、用途、展開モード、最終用途産業別-2025年~2030年の世界予測Artificial Intelligence in Computer Vision Market by Component, Technology, Function, Application, Deployment Mode, End-Use Industry - Global Forecast 2025-2030 |
||||||
カスタマイズ可能
適宜更新あり
|
コンピュータビジョンにおける人工知能市場:コンポーネント、技術、機能、用途、展開モード、最終用途産業別-2025年~2030年の世界予測 |
出版日: 2025年04月01日
発行: 360iResearch
ページ情報: 英文 195 Pages
納期: 即日から翌営業日
|
コンピュータビジョンにおける人工知能市場は、2023年に261億1,000万米ドルと評価され、2024年にはCAGR 24.02%で321億2,000万米ドルに成長し、2030年には1,178億9,000万米ドルに達すると予測されています。
主な市場の統計 | |
---|---|
基準年 2023 | 261億1,000万米ドル |
推定年 2024 | 321億2,000万米ドル |
予測年 2030 | 1,178億9,000万米ドル |
CAGR(%) | 24.02% |
人工知能はコンピュータ・ビジョンの技術革新の基本的な推進力として台頭し、従来の画像処理と知覚技術を洗練された自動化されたプロセスに変えてきました。近年、AIを活用したコンピュータ・ビジョン・ソリューションは、産業界が視覚データをどのように取得、分析、活用するかに革命をもたらしています。この変革は、製品開発やサービス提供を再構築するだけでなく、精度と効率に関する新たな運用基準を確立しています。
ディープラーニング、機械学習、リアルタイム処理の進歩により、システムは膨大なデータセットから学習することができるようになり、画像認識、物体追跡、文脈の理解が向上しました。企業がこれらの進化する技術の力を活用することで、自律航行、品質検査、監視などの複雑な課題に対処するための設備がより整っています。コンピュータビジョンにおけるAIの統合は、戦略を再考し、ワークフローを最適化し、革新的なアプリケーションを通じて将来の市場動向を予測する業界を後押ししています。
この概説書の目的は、AIがコンピュータビジョンの領域をどのように再活性化し、変革を促し、ビジネス成長の新たな道を切り開いたかについて、明確かつ包括的な視点を提供することです。技術シフトの急速なペースは、効率性の向上だけでなく、まったく新しい市場セグメントや機会の創出も約束し、企業が競争の激しい世界情勢の中で優位に立ち続けることを確実にします。
変革のシフト:技術の進歩がコンピュータビジョンの情勢をどのように再定義しているか
近年の技術進化は、コンピュータビジョンの展望に大きな変化をもたらしました。最先端の神経科学、高度なセンサー技術、計算能力の向上が戦略的に融合することで、画像処理と認識における更なる革新が促進されました。AI主導の機能を従来のコンピュータビジョンモデルと統合する能力により、製造、ヘルスケア、自動車、小売の各分野で、ビジネスプロセスの合理化が可能になりました。
ハードウェア・コンポーネントとソフトウェア・コンポーネントのシームレスな統合は今や標準となっており、多くの組織がリアルタイム・データとクラウドベースの展開を活用した、より俊敏で適応性の高いモデルへと移行しています。高解像度センサー、専用AIアルゴリズム、適応ミドルウェアのこの連携は、デジタル視覚データの取得と分析方法を再定義しました。その影響は、より迅速で正確な意思決定が不可欠な自律走行車からセキュリティ監視に至るまで、さまざまな業界に及んでいます。
企業がスピードとスケーラビリティを重視した革新的なモデルに軸足を移す中、ディープラーニングとコンピュータビジョンの融合は、かつてはSFの専売特許と考えられていた機能強化を後押ししています。企業は現在、日々の業務を改善するだけでなく、こうした変革的なシフトを活用することで、潜在的な市場機会を解き放つことができる立場にあります。
主要なセグメンテーションの洞察多面的な市場において多様な視点を照らし出す
コンピュータビジョン市場は、技術、アプリケーション、業界要件の微妙な相互作用を捉えるために、綿密にセグメント化されています。コンポーネントに基づくセグメンテーションを検討する場合、市場はハードウェア、サービス、ソフトウェアにまたがって分析されます。この中で、ハードウェアはカメラやセンサーの詳細な調査を含み、サービスカテゴリーは新技術の採用者を強化するためのコンサルティングやトレーニングを調査しています。ソフトウェアは、生データを実用的な洞察に変換するのに不可欠なAIアルゴリズムとミドルウェアに分類されます。
さらに、技術に基づくセグメンテーションでは、ステレオビジョンと構造化光に焦点を当てた3Dコンピュータビジョンから、畳み込みニューラルネットワークと再帰的ニューラルネットワークに体系的に分類されたディープラーニングまで、階層的な視点が提供されます。さらに、機械学習を教師あり学習と教師なし学習に分類し、音声認識とテキスト解析がより広範な文脈理解に貢献する自然言語処理によって補完します。
機能的セグメンテーションを分析することで、識別、位置特定、再構築、追跡などのプロセスがどのように最適化されるかが明らかになります。例えば、識別は人間検出と物体検出の両方をカバーし、ローカリゼーションは屋内と屋外のマッピングシナリオに及ぶ。セグメンテーションの旅は、環境と表面の詳細に焦点を当てた再構築で続き、行動と動きのパターンを監視するトラッキングが続きます。さらに、アプリケーション別のセグメンテーションには、3Dモデリング、ジェスチャー認識、画像認識、マシンビジョンなどの側面が含まれ、展開モードはクラウドベースとオンプレミスのセットアップで検討されます。最後に、自動車、ヘルスケア、製造業、小売業、セキュリティ・監視など、最終用途産業別のセグメンテーションを行い、それぞれ独自の要求と技術的前提条件を持っています。
The Artificial Intelligence in Computer Vision Market was valued at USD 26.11 billion in 2023 and is projected to grow to USD 32.12 billion in 2024, with a CAGR of 24.02%, reaching USD 117.89 billion by 2030.
KEY MARKET STATISTICS | |
---|---|
Base Year [2023] | USD 26.11 billion |
Estimated Year [2024] | USD 32.12 billion |
Forecast Year [2030] | USD 117.89 billion |
CAGR (%) | 24.02% |
Artificial Intelligence has emerged as a fundamental driver of innovation in computer vision, transforming traditional imaging and perception techniques into sophisticated, automated processes. In recent years, AI-powered computer vision solutions have revolutionized how industries capture, analyze, and act upon visual data. This transformation is not only reshaping product development and service delivery but also establishing new operational benchmarks for accuracy and efficiency.
Advancements in deep learning, machine learning, and real-time processing have allowed systems to learn from vast datasets, resulting in improved image recognition, object tracking, and contextual understanding. As companies harness the power of these evolving technologies, they remain better equipped to address complex challenges such as autonomous navigation, quality inspection, and surveillance. The integration of AI in computer vision is propelling industries to rethink strategies, optimize workflows, and anticipate future market trends through innovative applications.
The goal of this overview is to provide a clear and comprehensive perspective on how AI has reinvigorated the realm of computer vision, driving transformative change and opening up new avenues for business growth. The rapid pace of technological shifts promises not only enhanced efficiency but also the creation of entirely new market segments and opportunities, ensuring that enterprises continue to stay ahead in a competitive global landscape.
Transformative Shifts: How Technological Advancements Are Redefining the Computer Vision Landscape
Recent technological evolutions have led to profound changes in the computer vision landscape. A strategic convergence of cutting-edge neuroscience, advanced sensor technologies, and increased computational power has catalyzed further innovations in image processing and recognition. The capacity to integrate AI-driven features with traditional computer vision models has enabled businesses to streamline processes in manufacturing, healthcare, automotive, and retail sectors.
Seamless integration between hardware and software components is now standard, and many organizations are transitioning to more agile, adaptive models that leverage real-time data and cloud-based deployments. This alignment of high-resolution sensors, dedicated AI algorithms, and adaptive middleware has redefined how digital visual data is captured and analyzed. The impact is resonating across multiple industries, from autonomous vehicles to security monitoring, where faster, more accurate decision-making is essential.
As firms pivot to innovative models that emphasize speed and scalability, the fusion of deep learning and computer vision is driving enhancements that were once thought to be the exclusive domain of science fiction. Companies are now positioned to not only improve day-to-day operations but also to unlock latent market opportunities by harnessing these transformative shifts.
Key Segmentation Insights: Illuminating Diverse Perspectives in a Multifaceted Market
The computer vision market has been meticulously segmented to capture the nuanced interplay of technology, application, and industry requirements. When examining segmentation based on components, the market is analyzed across hardware, services, and software. In this context, hardware encompasses detailed studies of cameras and sensors, while the services category explores consulting and training to empower adopters of new technologies. Software is dissected further into AI algorithms and middleware, which are vital in translating raw data into actionable insights.
Furthermore, segmentation based on technology offers a layered perspective that spans from 3D computer vision-with additional focus on stereo vision and structured light-to deep learning, which is systematically divided into convolutional neural networks and recursive neural networks. The narrative continues with machine learning segmented in terms of supervised and unsupervised learning, complemented by natural language processing, where speech recognition and text analysis contribute to broader contextual understanding.
Analyzing functional segmentation reveals how processes such as identification, localization, reconstruction, and tracking are optimized. For example, identification covers both human and object detection, while localization extends to indoor and outdoor mapping scenarios. The segmentation journey continues with reconstruction, focusing on environment and surface details, followed by tracking, where behavioral and motion patterns are monitored. Additionally, segmentation by application includes facets such as 3D modeling, gesture recognition, image recognition, and machine vision, while deployment modes are examined in cloud-based versus on-premises setups. Finally, segmentation by end-use industry spans automotive, healthcare, manufacturing, retail, and security and surveillance, each with its own unique demands and technological prerequisites.
Based on Component, market is studied across Hardware, Services, and Software. The Hardware is further studied across Cameras and Sensors. The Services is further studied across Consulting and Training. The Software is further studied across AI Algorithms and Middleware.
Based on Technology, market is studied across 3D Computer Vision, Deep Learning, Machine Learning, and Natural Language Processing. The 3D Computer Vision is further studied across Stereo Vision and Structured Light. The Deep Learning is further studied across Convolutional Neural Networks and Recursive Neural Networks. The Machine Learning is further studied across Supervised Learning and Unsupervised Learning. The Natural Language Processing is further studied across Speech Recognition and Text Analysis.
Based on Function, market is studied across Identification, Localization, Reconstruction, and Tracking. The Identification is further studied across Human Identification and Object Identification. The Localization is further studied across Indoor Mapping and Outdoor Mapping. The Reconstruction is further studied across Environment Reconstruction and Surface Reconstruction. The Tracking is further studied across Behavior Tracking and Motion Tracking.
Based on Application, market is studied across 3D Modeling, Gesture Recognition, Image Recognition, and Machine Vision.
Based on Deployment Mode, market is studied across Cloud-Based and On-Premises.
Based on End-Use Industry, market is studied across Automotive, Healthcare, Manufacturing, Retail, and Security & Surveillance.
Key Regional Insights: Navigating Market Dynamics Across Diverse Global Regions
The geographical spread of the computer vision market accentuates the varying dynamics and opportunities in different regions. In the Americas, robust investments in technology and infrastructure are propelling advancements, driving a surge in the adoption of AI-driven visual systems across diverse industrial sectors.
In the Europe, Middle East & Africa region, historical innovation combined with a focus on regulatory frameworks and sustainable growth is paving the way for tailored implementations of computer vision solutions. The region is rapidly evolving with collaborative initiatives that integrate academic research with practical, real-world applications.
Meanwhile, the Asia-Pacific region stands out for its rapid digitization imperatives and expansive production ecosystems, which serve as both a crucible for innovation and a significant market in their own right. As these regions continue to contribute distinctively to the market landscape, they collectively shape a vibrant, multifaceted market that is geared to address both local and global technological challenges.
Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.
Key Companies Insights: Leaders Driving the Future of Computer Vision
A wide spectrum of companies is steering the advancement of computer vision across various domains by investing in research and pushing the boundaries of technological innovation. Dominant players such as Adobe Inc. and Advanced Micro Devices, Inc. have leveraged their engineering capabilities to integrate powerful visual computing capabilities into mainstream applications. Giants like Amazon Web Services, Inc. and Apple Inc. have redefined infrastructure and consumer experience by employing scalable models and state-of-the-art devices.
Innovative entities like Arm Limited and Basler AG have established a strong foundation in hardware performance, while Clarifai, Inc. and Cognex Corporation are at the forefront of developing breakthrough imaging software and analytical solutions. Similarly, global conglomerates such as Fujitsu Limited, Google LLC by Alphabet Inc., and Hailo Technologies Ltd. continue to push the innovation envelope through strategic investments and collaborative ventures. Huawei Technologies Co., Ltd. and Infosys Limited have also made significant strides in integrating cutting-edge computer vision tools within business ecosystems.
Continued contributions from Intel Corporation, International Business Machines Corporation, Landing AI, and LXT AI Inc. underscore the collaborative efforts toward streamlining operational efficiencies. With further advancements from Meta Platforms, Inc., Microsoft Corporation, and NetApp, Inc., the competitive landscape is constantly evolving. Noteworthy progress by Nvidia Corporation, Oracle Corporation, Qualcomm Technologies, Inc., and Raydiant Inc. complements a dynamic environment that is further enriched by initiatives from Samsung Electronics Co. Ltd., TechSee Augmented Vision Ltd., Unity Software Inc., and Wovenware, Inc. Finally, strategic interventions from Maxar Technologies Inc. and XenonStack Pvt. Ltd. highlight the sector's focus on innovative, data-driven approaches.
The report delves into recent significant developments in the Artificial Intelligence in Computer Vision Market, highlighting leading vendors and their innovative profiles. These include Adobe Inc., Advanced Micro Devices, Inc., Amazon Web Services, Inc., Apple Inc., Arm Limited, Basler AG, Clarifai, Inc., Cognex Corporation, Fujitsu Limited, Google LLC by Alphabet Inc., Hailo Technologies Ltd., Huawei Technologies Co., Ltd., Infosys Limited, Intel Corporation, International Business Machines Corporation, Landing AI, LXT AI Inc., Meta Platforms, Inc., Microsoft Corporation, NetApp, Inc., Nvidia Corporation, Oracle Corporation, Qualcomm Technologies, Inc., Raydiant Inc., Samsung Electronics Co. Ltd., TechSee Augmented Vision Ltd., Unity Software Inc., Wovenware, Inc. by Maxar Technologies Inc., and XenonStack Pvt. Ltd.. Actionable Recommendations: Strategic Directions for Industry Leaders in Computer Vision
To sustain competitive advantage in an increasingly complex technological ecosystem, leaders must adopt a multi-dimensional strategy. It is essential to prioritize investments in research and development while embracing a flexible approach that allows for rapid adaptation to field innovations. Emphasizing a balance between in-house development and strategic partnerships can accelerate product innovation and reduce time-to-market gaps.
Leaders are encouraged to actively leverage emerging trends such as deep learning and advanced sensor technologies, while also focusing on strengthening the hardware-software ecosystem. By closely monitoring regional market dynamics and regional differences, organizations can tailor solutions that address localized needs. Moreover, investing in cloud-based deployment models will enhance scalability and resilience, ensuring sustained performance even in rapidly evolving industry environments.
Another critical recommendation is the integration of comprehensive training initiatives and effective knowledge transfer programs to upskill workforce across various technical domains, ultimately leading to higher productivity and innovation momentum.
Conclusion: Embracing Change and Harnessing Innovation in the Computer Vision Space
In summary, artificial intelligence has ushered in a new era in computer vision, marked by significant advancements that enhance precision, efficiency, and operational effectiveness. The multifaceted segmentation analysis highlights the intricacies of component design, technological evolution, functional deployments, application areas, and industry-specific requirements. Each segment reinforces the transformative nature of AI-driven computer vision technologies, offering unparalleled opportunities for growth and competitive differentiation.
The insights derived from regional studies and prominent corporate contributions further underscore the necessity for organizations to adapt swiftly to the emerging trends. The convergence of diverse technological components coupled with dynamic market strategies is paving the way for robust performance improvements across multiple industries. As challenges persist, forward-thinking leaders will continue to drive meaningful change by embracing innovative solutions that not only resolve current operational inefficiencies but also set the foundation for sustained future success.