This video follows a thief's movements, using the data from the purloined iPhone itself.

Sue Huang's phone was stolen, and she recovered it five days later, ransoming it from the thief who took it. But the story doesn't end there. She and Brian House used OpenPaths and Google Street View images to recreate the phones movements in video. As Brian explains on his blog:

We had a collection of points that the thief had visited with the phone, so I thought we should be able to get a smooth path between them.

First, I used the Google Directions API to map the likely route that the thief would have taken between known locations, as well as filling in some intermediary points, which was @blprnt's idea from our earlier brainstorms. One of the cool things about the Street View panorama data (described by @jaimethompson) is that it shows the linkages between consecutive images taken by the Google car. So by calculating the heading from one point to the next and heuristically choosing links between panoramas headed in the right direction, we can access all the images taken along the way. Again using heading we can point the camera in the right direction, download the tiles we want, and stitch a frame together.

Brian says it's sort of like Google is driving the getaway car. I prefer to think of it as the chase vehicle.