What you are talking about is called Monocular SLAM. The process of calculating the trajectory inherently maps the world at the same time by estimating feature

What you are talking about is called Monocular SLAM. The process of calculating the trajectory inherently maps the world at the same time by estimating feature positions by inter-frame distances. It really isn't a problem to use video frames, but they have different types of error/noise to high res stills. For example, the video camera is moving, and it has rolling shutter, so every pixel (or pixel row) is from a different orientation. If this isn't accounted for it introduces noise, but doing so takes more/better processing. But video frames have consistent intre-frame delay and good coherence, so it is easier to match features frame-by-frame than from a heap of individual photos. If you have good (hot GPS) positions then that makes both situations easier. Model visual quality is improved by better resolution pictures in a fairly straightforward way... But you can get the same data by physically moving a lower res camera closer to all surfaces. It is just harder to scan quickly and maintain track if you have to do that. Some people even put lenses in front of their depth camera to zoom in tighter, for capturing finer detail.