I watched The Clock at the Boston Museum of Fine Arts from about 4:45 to 6:30 on Friday. My thoughts on The Clock:
The experiment works in part because scenes with clocks in them are usually frenetic. In a movie, the presence of a clock usually means someone is in a rush, and so most of the sequences convey urgency.
It’s often hard to spot the clock in each scene. In less exciting sequences, this serves as a game to pass the time. In many cases the clock in question is never in focus, or is moving too fast for the viewer to notice. The editors must have done careful freeze-frames and zoomed in on wristwatches to work out the indicated time.
The selected films are mostly in English, with a fair number in French and very few in any other languages. This feels fairly arbitrary to me.
Scenes from multiple films are often mixed within each segment. It seems like the editors adopted a relaxed rule, maybe something like: “if a clock appeared in an original, then a one minute window around the moment of appearance is fair game to include during that minute of The Clock, spliced together with other clips in any order”.
The editing makes heavy use of L cuts and audio crossfades to make the fairly random assortment of sources feel more cohesive.
I swear I saw a young Michael Cain at least twice in two different roles.
Some of the sources were distinctly low-fidelity, often due to framerate matching issues. I think this might be the first production I’ve seen that would really have benefited from a full Variable Frame Rate render and display pipeline.
I started to wonder about connections to deep learning. Could we train an image captioning network to identify images of clocks and watches, then run it on a massive video corpus to generate The Clock automatically?
Or, could we construct a spatial analogue to The Clock’s time-for-time conceit? How about a service that notifies you of a film clip shot at your current location? With a large GPS-tagged corpus (or a location-finder neural network) it might be possible to do this with pretty broad coverage.