  Time-to-contact (TTC), the time for an object to collide with the observer's
plane, is a powerful tool for path planning: it is potentially more informative
than the depth, velocity, and acceleration of objects in the scene -- even for
humans. TTC presents several advantages, including requiring only a monocular,
uncalibrated camera. However, regressing TTC for each pixel is not
straightforward, and most existing methods make over-simplifying assumptions
about the scene. We address this challenge by estimating TTC via a series of
simpler, binary classifications. We predict with low latency whether the
observer will collide with an obstacle within a certain time, which is often
more critical than knowing exact, per-pixel TTC. For such scenarios, our method
offers a temporal geofence in 6.4 ms -- over 25x faster than existing methods.
Our approach can also estimate per-pixel TTC with arbitrarily fine quantization
(including continuous values), when the computational budget allows for it. To
the best of our knowledge, our method is the first to offer TTC information
(binary or coarsely quantized) at sufficiently high frame-rates for practical
use.
