Researchers in the lab of UC Santa Barbara professor Yasamin Mostofi have enabled, for the first time, determining whether the person behind a wall is the same individual who appears in given video footage, using only a pair of WiFi transceivers outside.
This novel video-WiFi cross-modal gait-based person identification system could have a variety of applications, from surveillance and security to smart homes. For instance, consider this scenario. Law enforcement has a video footage of a robbery. They are suspicious that the robber is hiding in a house. Can a pair of WiFi transceivers outside of the house identify the person in the house and determine if it is the same person as in the robbery video? The researchers proved that it is possible.
This new technique can determine if the person behind the wall is the same as the one in a video footage, by using only a pair of off-the-shelf WiFi transceivers outside.
This system only uses the received power measurements of a pair of WiFi transceivers. It does not need any prior WiFi or video training data of the person to be identified.
And, it does not need any prior knowledge of the operation area or person’s track. It can identify people through walls.
Identifying a person through walls from candidate video footage is a considerably challenging problem. The way each one of us move is unique. In other words, as a person moves, the way different body parts move with respect to each other can be a unique identifier of the person.
This new system is able to properly capture and compare the gait information content of the video and WiFi signals to establish if they belong to the same person.
News Source: UCSB
