<story><title>Identifying a person through walls from video footage, using only WiFi</title><url>https://techxplore.com/news/2019-10-method-enables-person-walls-candidate.html</url></story><parent_chain></parent_chain><comment><author>simias</author><text>Judging by the video they achieve 83% success rate with a pool of 8 people in what looks like perfect conditions (only one person, no perturbation of any kind etc...). The video also states, rather suspiciously IMO, that &amp;quot;This scene on the other side is shown solely for presentation and was not used for identification&amp;quot;. Why not show the actual footage of the experiment?&lt;p&gt;&amp;gt;The lab has tested their new technology on 1,488 WiFi-video pairs, drawn from a pool of eight people, and in three different behind-wall areas, and achieved an overall accuracy of 84% in correctly identifying the person behind the wall.&lt;p&gt;What does it mean exactly? They only need one short video and one short wifi capture to get 84% success rate? That&amp;#x27;s what the video seems to imply but I find that very hard to believe. Or maybe it&amp;#x27;s just because it&amp;#x27;s fairly easy to distinguish among 8 people (especially if they have significantly different body types) and it won&amp;#x27;t work quite as well at large. I can identify my girlfriend&amp;#x27;s footsteps in the staircase with remarkable accuracy but I can guarantee you that it won&amp;#x27;t scale to the general population.&lt;p&gt;Maybe it works better than I give it credit for but they need to bring up better evidence IMO.</text></comment>
<story><title>Identifying a person through walls from video footage, using only WiFi</title><url>https://techxplore.com/news/2019-10-method-enables-person-walls-candidate.html</url></story><parent_chain></parent_chain><comment><author>spydum</author><text>So basically gait analysis using WiFi power levels. At present requires making the user walk through a specific choke point to measure the gait, then can compare any other captured video to compare. Pretty neat!</text></comment>