Europe AI in Computer Vision Market Forecast to 2027 - COVID-19 Impact and Regional Analysis by Component and End-User

The AI in computer vision market in Europe is expected to grow from US$ 1,212.90 million in 2019 to US$ 27,107.46 million by 2027; it is estimated to grow at a CAGR of 47.4% from 2020 to 2027.

Nowadays, any virtual reality (VR) or augmented reality (AR) device produces an interactive 3D world. Most AR devices can conduct basic environment scans. For example, Google ARCore can detect flat surfaces and changes in light conditions, and VR systems can detect the user's movements by head tracking and controllers; however, their abilities stop there. The program for computer vision moves VR and AR to the next level of progress that some call merged reality (MR). With the aid of external environment mapping cameras and sensors, as well as eye-tracking solutions and gyroscopes to position the user, the VR and AR systems can perceive the atmosphere and direct the user away from barriers such as walls, products, or other users; detect the movement of the user's eye and body and adopt the VR environment accordingly; and offer instructions and directions for indoor areas, public parks, underground, and more. For instance, at Lowe's hardware store, each visitor can use an AR system to make their shopping list from which they can get directions for each item in the store. This is expected to raise the demand for artificial intelligence (AI) in computer vision over the years. Additionally, increase in demands for Emotion AI is a major factor driving the Europe AI in computer vision market. Based on end-user, the automotive segment led the Europe AI in computer vision market in 2019. In camera-enabled automotive security, vision-processing IP plays a vital role, especially in autonomous vehicles and ADAS applications. Vision products in automotive applications help improve the driving experience. Computer vision is used by driver control systems to ensure that the driver stays alert and awake while the vehicle is running. If the driver is feeling drowsy, these systems will track head movement and body language, thereby posing a danger to those on the lane. They can also monitor driver activities and behavior such as texting and eating, and respond or alert the driver with a friendly reminder that encourages the individual to focus on the road instead. Similarly, artificial intelligence powered computer vision solutions are also being highly adopted across autonomous vehicles. In autonomous vehicles, computer vision is often called "perception” because cameras are the main tool that the vehicles use to analyze its environment. Thus, the above-mentioned factors are contributing to the high adoption of the technology across the automotive sector.

As selected countries observed a rise in the number of reported cases and subsequently attracted strict as well as longer lockdown periods or social isolation, the effect of COVID-19 varied from country to country throughout the European region. However, due to the strong healthcare system, Western European countries such as Germany, France, Russia, and the UK have seen a comparatively modest decrease in their development activities. To protect their population from the virus, European governments have made huge investments in the implementation of technology in their healthcare systems for better detection of symptoms of the virus. AI in computer vision is being adopted across the healthcare industry in the region to efficiently detect and treat COVID-19 among the population, thereby leaving a positive impact on the market. However, due to the temporary shutdown of all economic activities in the region, the adoption of technologies has experienced a dip across all other major industries in the region such as manufacturing, retail and automotive. This is further expected to restrain the market growth over the years. Thus, the outbreak of the virus is expected to have a moderate to low impact on the AI in computer vision market in the region.

The overall Europe AI in computer vision market size has been derived using both primary and secondary sources. To begin the research process, exhaustive secondary research has been conducted using internal and external sources to obtain qualitative and quantitative information related to the market. The process also serves the purpose of obtaining an overview and forecast for the Europe AI in computer vision market with respect to all the segments pertaining to the region. Also, multiple primary interviews have been conducted with industry participants and commentators to validate the data, as well as to gain more analytical insights into the topic. The participants who typically take part in such a process include industry experts, such as VPs, business development managers, market intelligence managers, and national sales managers along with external consultants, such as valuation experts, research analysts, and key opinion leaders specializing in the Europe AI in computer vision market. 1.6 Xilinx, Inc.; Allied Vision Technologies GmbH; Basler AG; Cognex Corporation; General Electric Company; Intel Corporation; Microsoft Corporation; Nvidia Corporation; Qualcomm Incorporated; and Teledyne Technologies, Inc are among the key players operating in the Europe AI in computer vision market.

Reasons to Buy

• Save and reduce time carrying out entry-level research by identifying the growth, size, leading players, and segments in the Europe AI in computer vision market
• Highlights key business priorities in order to assist companies to realign their business strategies
• The key findings and recommendations highlight crucial progressive industry trends in the Europe AI in computer vision market, thereby allowing players across the value chain to develop effective long-term strategies
• Develop/modify business expansion plans by using substantial growth offering developed and emerging markets
• Scrutinize in-depth Europe market trends and outlook coupled with the factors driving the AI in computer vision market, as well as those hindering it
• Enhance the decision-making process by understanding the strategies that underpin commercial interest with respect to client products, segmentation, pricing and distribution