Perception is the capability of a system to organize and interpret sensory data to represent and understand the underlying information. Much of the perception relies on multi-modal sensing, while the building principles of perception, such as learning and identifying patterns, apply across the visual spectrum, text, audio, and more recently, wireless signals.
As the field of computer vision becomes increasingly more refined and practical, the scope of research efforts is also growing to undertake more challenging problems, often those that would benefit from the incorporation of additional modalities to have a crucial impact on our daily lives. Applications such as monitoring people and spaces are now within reach of visual perception methods that can effectively extend beyond photons of the visible spectrum to wireless signals of the electromagnetic waves traveling through the air. Hence, there is an increasing interest in the computer vision community establishing interdisciplinary research lines to analyze and leverage wireless sensory data in a growing number of ways.
In stark contrast to existing sensing modalities such as color or infrared images, wireless data based upon 5G, WiFi, millimeter waves, and radar allow for the perception of the environment, changes, and 3D structure of static or dynamic scenes through absolute darkness, through occluders, walls and around corners. Even subtle and distant motions invisible to cameras, such as heart rate and respiration, can be perceived through the electromagnetic field. Wireless systems are already an integral part of mobile devices and network access points in many households and offices. Using radio frequencies as a new type of camera allows improving existing algorithms developed in computer vision and machine learning for photometric images and facilitates inventing an entirely new generation of solutions that use wireless signals to their full potential for widespread applications.
This workshop is being held at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022, New Orleans, Lousiana. Its objective is to highlight cutting-edge approaches and recent progress in the growing field of joint wireless perception using machine learning and possibly also other modalities such as images. It will allow researchers and companies in wireless perception to present their progress and discuss novel ideas that will shape the future of this area..