$Q

We introduce $Q, a super-quick, articulation-invariant point-cloud stroke-gesture recognizer for mobile, wearable, and embedded devices with low computing resources. $Q ran up to 142X faster than its predecessor $P in our benchmark evaluations on several mobile CPUs, and executed in less than 3% of $P's computations without any accuracy loss. In our most extreme evaluation demanding over 99% user-independent recognition accuracy, $P required 9.4s to run a single classification, while $Q completed in just 191ms (a 49X speed-up) on a Cortex-A7, one of the most widespread CPUs on the mobile market. $Q was even faster on a low-end 600-MHz processor, on which it executed in only 0.7% of $P's computations (a 142X speed-up), reducing classification time from two minutes to less than one second. $Q is the next major step for the "$-family" of gesture recognizers: articulation-invariant, extremely fast, accurate, and implementable on top of $P with just 30 extra lines of code.