The frame or image of a video stream of a videoconference is divided into a series of segments for analysis. There is a primary grid, which covers the entire frame, and an alternate grid, which is shifted from the primary grid. Each segment is small enough to allow a neural network to efficiently operate on the segment without requiring downsampling. By operating on full resolution images, a participant can be identified at a greater distance from the camera. The entire frame is analyzed at a lower frequency, such as once per five seconds, but each segment containing a participant in the conference is scanned at a higher frequency, such as once per second, to maintain responsiveness to participant movement but also allow the full resolution operation.