全球视觉处理单元 (VPU) 市场规模（按架构、应用、最终用户产业、地区、范围和预测）

视觉处理单元 (VPU) 市场规模及预测

2023 年视觉处理单元 (VPU) 市场规模价值 21.17 亿美元，预计在预测期 (2024-2030 年) 内将以 17.26% 的复合年增长率增长，到 2030 年达到 75.59 亿美元。达到100万美元。

视觉处理单元 (VPU) 的全球市场推动因素

视觉处理单元 (VPU) 市场的市场推动因素会受到多种因素的影响。

人工智慧和机器学习的发展：随着消费性电子、零售、医疗保健和汽车等行业对基于人工智慧的应用的需求不断增长，高效分析大量视觉数据的需求也在增长。诸如VPU 之类的硬体变得越来越必要。

边缘运算的兴起边缘运算的兴起是指更靠近源头处理数据，而不是将资料集中在资料中心进行处理。在工业自动化、自动驾驶汽车和监控系统等应用中，VPU 对于即时处理边缘视觉输入以实现更快的决策和低延迟至关重要。

电脑视觉的应用日益广泛：电脑视觉的应用正在扩展到许多领域，包括医学影像、农业监测、物体检测和脸部辨识。 VPU 对于这些应用程式的运作至关重要，因为它们可以加速影像处理并使硬体能够立即响应视觉输入。

对物联网设备和智慧相机的需求不断增加：物联网 (IoT) 设备和智慧相机的兴起推动了对能够有效处理复杂影像且功耗更低的 VPU 的需求。 VPU 可实现本地记录、分析和对视觉输入的操作，从而使这些设备无需持续的互联网连接和云端处理。

无人机和自动驾驶汽车的成长：电脑视觉技术越来越多地应用于无人机和汽车行业，用于手势识别、障碍物检测和导航等功能。 VPU 在汽车和无人机中发挥着至关重要的作用，使它们能够高速、准确地评估视觉输入并做出即时决策。

对节能解决方案的需求：随着电池供电产品市场的扩大，硬体设计中的能源效率变得越来越重要。 VPU 旨在以最小的功耗提供最大的效能，使其成为穿戴式装置、智慧型手机和物联网感测器等电池供电设备的理想选择。

快速创新：半导体公司不断提出新想法来提高 VPU 的效能和效能。人工智慧加速器、神经处理单元 (NPU) 和用于特定电脑视觉任务的专用硬体的整合等进步正在推动 VPU 的进步及其在多个垂直领域应用的扩展。

限制全球视觉处理单元 (VPU) 市场的因素

有几个因素可能会对视觉处理单元（VPU）市场造成限制和课题。

开发成本高：设计和製造 VPU 所涉及的研发和测试成本很高。这可能会打击新创企业和中小企业的积极性，降低市场竞争力和创新能力。

整合复杂性：将 VPU 整合到当前系统和设备中非常困难且耗时，尤其是在对功率、尺寸和效能有严格要求的情况下。此外，它们可能需要专业知识或存在相容性问题。

熟练劳动力有限：很难找到具有 VPU 设计、最佳化和应用程式开发经验的专家。这种短缺会减缓创新和采用的努力，特别是在缺乏训练有素的劳动力的地区和经济部门。

资料安全和隐私：VPU 处理大量敏感资料（例如照片和影片）这一事实引发了资料安全和隐私问题。实施强有力的安全措施和法规合规性（例如 GDPR）使得 VPU 部署更加复杂和昂贵。

效能瓶颈：儘管有所改进，但 VPU 仍然存在效能问题，尤其是在需要高精度和准确度的情况下，或在即时应用中。克服这些限制并保持效率和低功耗仍然是一个课题。

市场分散和标准化：VPU市场相对分散，许多供应商提供各种产品和解决方案。这种碎片化可能导致互通性问题和缺乏标准化，使得客户难以选择最适合其个人需求的 VPU。

环境问题：VPU 在製造和处理过程中使用稀土金属和危险化合物，可能产生与其他电子元件类似的环境影响。对于 VPU 製造商来说，透过永续实践解决这些环境问题又增加了另一层复杂性。

与替代技术竞争：专用 ASIC（专用积体电路）、CPU 和 GPU 是与 VPU 竞争的一些替代技术。根据应用需求，这些替代技术可能提供类似的性能或以更低的成本。这可能会对 VPU 的广泛采用构成课题。

目录

第 1 章简介

• 市场定义
• 市场区隔
• 研究方法

第 2 章执行摘要

• 主要发现 市场概况 市集亮点

第三章 市场概览

• 市场规模与成长潜力
• 市场趋势
• 市场推动因素
• 市场限制
• 市场机会
• 波特五力分析

• 嵌入式视觉处理单元
• 独立 VPU
• 混合 VPU（CPU、GPU 与 VPU 的组合）

第 5 章。

• 物体侦测
• 影像识别
• 影像处理
• 模式识别

第 6 章：按最终用户产业划分的视觉处理单元 (VPU) 市场

• 汽车
• 家用电器
• 医疗保健
• 安全与监控
• 工业 航空航太和国防

第 7 章 区域分析

• 北美洲
• 美国
• 加拿大
• 墨西哥
• 欧洲
• 英国
• 德国
• 法国
• 义大利 亚太地区
• 中国
• 日本
• 印度
• 澳大利亚
• 拉丁美洲
• 巴西
• 阿根廷
• 智利
• 中东和非洲
• 南非
• 沙乌地阿拉伯
• 阿拉伯联合大公国

第 8 章 市场动态

• 市场推动因素
• 市场限制
• 市场机会
• COVID-19 对市场的影响

第 9 章 竞争格局

• 大型公司
• 市占率分析

第十章 公司简介

• Nvidia
• Intel
• Ambarella
• Qualcomm
• NXP Semiconductors
• Texas Instruments
• Samsung Electronics

第 11 章 市场展望与机会

• 新兴技术
• 未来市场趋势
• 投资机会

第 12 章附录

• 缩写列表
• 来源与参考文献

Vision Processing Unit Market Size And Forecast

Vision Processing Unit Market size was valued at USD 2117 Million in 2023 and is projected to reach USD 7559 Million By 2030, growing at a CAGR of 17.26% during the forecast period 2024 to 2030.

Global Vision Processing Unit Market Drivers

The market drivers for the Vision Processing Unit Market can be influenced by various factors. These may include:

Developments in AI and Machine Learning: As a result of the expanding requirement for AI-driven applications across a range of industries, including consumer electronics, retail, healthcare, and automotive, specialized hardware, such as VPUs, is becoming more and more necessary in order to analyze vast volumes of visual data effectively.

The rise of edge computing: The rise of edge computing refers to the practice of processing data closer to the data source instead of centrally located in a data center. In order to provide real-time processing of visual input at the edge and facilitate quicker decision-making and lower latency in applications like industrial automation, autonomous vehicles, and surveillance systems, VPUs are essential.

Growing Adoption of Computer Vision: Applications for computer vision are expanding to many fields, including medical imaging, agricultural monitoring, object detection, and facial recognition. VPUs are essential to the operation of these applications because they speed up picture processing and allow hardware to react instantly to visual input.

Increasing Need for IoT Devices and Smart Cameras: The increasing number of Internet of Things (IoT) devices and smart cameras is boosting the demand for VPUs that can efficiently process complex images while using less power. By enabling local recording, analysis, and action on visual input, VPUs allow these devices to do away with the requirement for continual internet connectivity and cloud processing.

Growth of Drones and Autonomous Vehicles: Computer vision technology is being used more and more in the drone and car industries for functions including gesture recognition, obstacle detection, and navigation. VPUs are crucial parts of these systems because they allow cars and drones to evaluate visual input fast and precisely so they can make decisions instantly.

Demand for Energy-efficient Solutions: Energy efficiency in hardware design is becoming more and more important as the market for battery-powered products expands. Because VPUs are made to maximize performance while consuming the least amount of power, they are a great fit for battery-operated devices like wearables, smartphones, and Internet of Things sensors.

Quick Technological Innovations: To increase the effectiveness and performance of VPUs, semiconductor companies are always coming up with new ideas. The progress of VPUs and the expansion of their applications across multiple industries are being propelled by advancements like the integration of AI accelerators, neural processing units (NPUs), and specialized hardware for particular computer vision tasks.

Global Vision Processing Unit Market Restraints

Several factors can act as restraints or challenges for the Vision Processing Unit Market. These may include:

High Development Costs: Research, development, and testing costs are high when designing and creating VPUs. This may discourage startups and smaller businesses, reducing market competitiveness and innovation.

Complexity of Integration: It can be difficult and time-consuming to integrate VPUs into current systems or devices, particularly in situations where there are strict requirements for power, size, or performance. Adoption hurdles include the need for specialist knowledge and compatibility problems.

Restricted Access to Skilled Labor: Professionals with experience in VPU design, optimization, and application development are hard to come by. Innovation and implementation efforts may be slowed down by this shortage, particularly in areas or sectors of the economy where access to trained labor is scarce.

Data security and privacy: Data security and privacy issues are brought up by the fact that VPUs process sensitive data, like photos and videos, a lot. VPU deployments become more complex and expensive when strong security measures and regulatory compliance, such as GDPR, are put in place.

Performance bottlenecks: Despite improvements, VPUs may still experience problems with performance, especially in situations that call for a high degree of accuracy and precision or in real-time applications. It is still difficult to get above these restrictions while keeping efficiency and low power usage.

Market Fragmentation and Standardization: There are many vendors offering a variety of products and solutions, resulting in a relatively fragmented VPU market. This fragmentation may result in problems with interoperability, a lack of standardization, and make it harder for customers to choose the best VPU for their individual requirements.

Environmental Concerns: Because rare earth metals and hazardous compounds are used in the production of VPUs and their disposal, there may be environmental effects similar to those of other electronic components. For VPU makers, addressing these environmental issues through sustainable practices introduces still another level of complexity.

Competition from Alternative Technologies: Specialized ASICs (Application-Specific Integrated Circuits), CPUs, and GPUs are some of the alternative technologies that compete with VPUs. These alternatives could provide similar performance or at a lower cost, depending on the needs of the application. This could provide a challenge to the broad adoption of VPUs.

Global Vision Processing Unit Market Segmentation Analysis

The Global Vision Processing Unit Market is segmented based on Architecture, Application, End-User Industry And Geography.

Vision Processing Unit Market, By Architecture

• Embedded VPUs: Compact VPUs integrated directly into devices for on-device processing with low power consumption.
• Standalone VPUs: Independent VPUs designed for specific processing tasks, often used in edge computing applications.
• Hybrid VPUs (Combining CPUs, GPUs, and VPUs): Systems that combine VPUs with other processing units like CPUs and GPUs to leverage the strengths of each for optimized performance in various applications.

Vision Processing Unit Market, By Application

• Object Detection: Utilizes VPUs for identifying and locating objects within images or video streams.
• Image Recognition: Involves the use of VPUs to classify and categorize images based on their content.
• Image Processing: VPUs are employed to enhance or manipulate images for various purposes such as filtering, resizing, or correcting.
• Pattern Recognition: VPUs are tasked with recognizing recurring patterns or structures within data, often used in fields like biometrics or quality control.

Vision Processing Unit Market, By End-User Industry

• Automotive: VPUs are integrated into vehicles for applications like autonomous driving, driver assistance systems, and in-vehicle infotainment.
• Consumer Electronics: VPUs power features in devices like smartphones, cameras, and augmented reality glasses, enabling tasks such as facial recognition and photo enhancement.
• Healthcare: Utilization of VPUs in medical imaging equipment for tasks like MRI or CT scan analysis, as well as in telemedicine and wearable health devices.
• Security and Surveillance: VPUs are used in CCTV systems and security cameras for tasks like real-time monitoring, facial recognition, and intruder detection.
• Industrial: VPUs find applications in industrial automation, quality control, and robotics, enabling tasks like defect detection, product tracking, and process optimization.
• Aerospace and Defense: VPUs are utilized in UAVs (drones), satellite imaging, military surveillance systems, and cockpit displays for tasks like target identification, navigation, and reconnaissance.

Vision Processing Unit Market, By Geography

• North America
• Europe
• Asia-Pacific
• Latin America
• Middle East & Africa

Key Players

• The major players in the Vision Processing Unit Market are:
• Nvidia
• Intel
• Ambarella
• Qualcomm
• NXP Semiconductors
• Texas Instruments
• Samsung Electronics

TABLE OF CONTENTS

1. Introduction

• Market Definition
• Market Segmentation
• Research Methodology

2. Executive Summary

• Key Findings
• Market Overview
• Market Highlights

3. Market Overview

• Market Size and Growth Potential
• Market Trends
• Market Drivers
• Market Restraints
• Market Opportunities
• Porter's Five Forces Analysis

4. Vision Processing Unit Market, By Architecture

• Embedded VPUs
• Standalone VPUs
• Hybrid VPUs (Combining CPUs, GPUs, and VPUs)

5. Vision Processing Unit Market, By Application

• Object Detection
• Image Recognition
• Image Processing
• Pattern Recognition

6. Vision Processing Unit Market, By End-User Industry

• Automotive
• Consumer Electronics
• Healthcare
• Security and Surveillance
• Industrial
• Aerospace and Defense

7. Regional Analysis

• North America
• United States
• Canada
• Mexico
• Europe
• United Kingdom
• Germany
• France
• Italy
• Asia-Pacific
• China
• Japan
• India
• Australia
• Latin America
• Brazil
• Argentina
• Chile
• Middle East and Africa
• South Africa
• Saudi Arabia
• UAE

8. Market Dynamics

• Market Drivers
• Market Restraints
• Market Opportunities
• Impact of COVID-19 on the Market

9. Competitive Landscape

• Key Players
• Market Share Analysis

10. Company Profiles

• Nvidia
• Intel
• Ambarella
• Qualcomm
• NXP Semiconductors
• Texas Instruments
• Samsung Electronics

11. Market Outlook and Opportunities

• Emerging Technologies
• Future Market Trends
• Investment Opportunities

12. Appendix

• List of Abbreviations
• Sources and References