Times Square.mp4

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Life is measured in time. The shortness of the duration of a life makes it that much more meaningful, every moment gaining value by being so fleeting and ephemeral. And yet, as we grow older, we find that we lose time more easily, something Douglas Hofstadter(1) believes is inevitable as we accumulate experiences and chunk larger and larger segments of our life. Research now suggests even on the very small time scale of minutes, the diversity of our visual experiences influences (2) our very perception of time. The videos I submit here are intended to help us experience that, to know what it means to lose time. And hopefully, providing with that sense an opportunity to reflect and gain time in the future.

As you watch the video please pay attention to your felt sense of time, because the first half of the video, while having the same content and same time duration as the second half, lacks the most salient, the most instinctively interesting portions of the visuals. How does time feel in the first compared to the second half of the video?

Technical Details: To begin with, a disclaimer, this video is not intended as a genuine scientific demonstration. I have identified the salient portions of each frame in the video (using the SaliencyToolbox, saliencytoolbox.net (3)), and then have taken some large scale liberties with how I use this information to remove parts of the images. Nonetheless, there is a loss of some salient qualities in every frame, simply without the rigor of science and instead created with what felt better. In the background, there plays music of decay as well. Anyone interested can contact me for the code to create a video of this nature with any video they may have.

References:
(1) Hofstadter, D. R. (2001). Analogy as the core of cognition. The analogical mind: Perspectives from cognitive science, 499-538.
(2) Roseboom, W., Fountas, Z., Nikiforou, K., Bhowmik, D., Shanahan, M., & Seth, A. K. (2019). Activity in perceptual classification networks as a basis for human subjective time perception. Nature communications, 10(1), 1-9.
(3) Walther, D., & Koch, C. (2006). Modeling attention to salient proto-objects. Neural networks, 19(9), 1395-1407.

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