Fujitsu Laboratories has developed a technology for compressing ultra-high-definition, high-volume video data to the minimum size needed for AI video recognition applications.
This technology can compress video data to just one-tenth the size of data prepared using conventional compression technology intended for visual confirmation by humans.
In recent years, there has been a sharp increase in demand for AI analysis of video data in various business areas. The spread of 5th-generation mobile communications system, in particular, is expected to contribute to an explosive increase in the number of ultra-high-definition video images captured by cameras, as well as many images captured on the street and on production lines.
In developing this new compression technology, Fujitsu focused on an important divergence in the way in which AI and humans recognize images. Namely, AI and humans tend to differ in the areas of the image that are emphasized as important for judgment when recognizing people, animals, or objects in video data. Fujitsu has developed a technology to automatically analyze the areas that AI values and to compress data to the minimum size that AI can recognize.
This makes it possible to analyze a large amount of video data without compromising recognition accuracy, and at the same time significantly reduce operating and data transmission costs. It is also anticipated that the technology will allow users to analyze more advanced video data by combining multiple video data stored in the cloud, sensor data, and performance data such as sales data.
Background and Challenges
In recent years, technology for analyzing images using AI has been developing rapidly and is expected to be one of the driving forces for digital transformation in many companies in a variety of industries. With the advent of sophisticated 5G mobile services in 2020, demand for AI analysis is expected to increase even further, accompanied by the increasing use of ultra-high-definition 4K and 8K cameras and large amounts of video data for applications including behavioral analysis in the manufacturing and retail industries.