commit 107ce707b5eaf8758806d456d07832c1db477555
author Philip Quinn <pquinn@google.com> Fri Jul 14 13:07:13 2023 -0700
committer Philip Quinn <pquinn@google.com> Fri Jul 21 17:25:54 2023 -0700
tree d8c98491a62ffbb262c8a84adf22340770af618f
parent 1bbb0a93c8fda9f7fe0384b6138030cdebdb3324

Update motion prediction model.

Input events with no movement (r = 0) are now included in the buffer
so that the model can accurately determine when the input device has
become stationary, and a noise floor is added to prevent spurious
predictions when this happens.

Benchmark results:
  Old:
    timeRecordAndPredict_mean (ns): 17990
    timeRecordAndPredict_median (ns): 18024
    timeRecordAndPredict_min (ns): 17606
    timeRecordAndPredict_standardDeviation: 345
  New:
    timeRecordAndPredict_mean (ns): 38394
    timeRecordAndPredict_median (ns): 38476
    timeRecordAndPredict_min (ns): 38083
    timeRecordAndPredict_standardDeviation: 187

Bug: 288354672
PiperOrigin-RevId: 549064247
Test: predictions are visible in the motionprediction test app
Test: atest CtsInputTestCases
Test: atest MotionPredictorBenchmark MotionPredictorTest
Test: atest --host libinput_tests
Change-Id: I6c3917591323d7117c4ee2e91abf6c6004178f19

libs/input/MotionPredictor.cpp

diff --git a/libs/input/MotionPredictor.cpp b/libs/input/MotionPredictor.cpp
index 68e6888..c2ea35c 100644
--- a/libs/input/MotionPredictor.cpp
+++ b/libs/input/MotionPredictor.cpp
@@ -138,7 +138,8 @@
     // Pass input event to the MetricsManager.
     if (!mMetricsManager) {
         mMetricsManager =
-                std::make_optional<MotionPredictorMetricsManager>(mModel->predictionInterval(),
+                std::make_optional<MotionPredictorMetricsManager>(mModel->config()
+                                                                          .predictionInterval,
                                                                   mModel->outputLength());
     }
     mMetricsManager->onRecord(event);
@@ -184,8 +185,18 @@
     const int64_t futureTime = timestamp + mPredictionTimestampOffsetNanos;
 
     for (int i = 0; i < predictedR.size() && predictionTime <= futureTime; ++i) {
-        // TODO(b/266747654): Stop predictions if confidence and/or predicted pressure are below
-        // some thresholds.
+        if (predictedR[i] < mModel->config().distanceNoiseFloor) {
+            // Stop predicting when the predicted output is below the model's noise floor.
+            //
+            // We assume that all subsequent predictions in the batch are unreliable because later
+            // predictions are conditional on earlier predictions, and a state of noise is not a
+            // good basis for prediction.
+            //
+            // The UX trade-off is that this potentially sacrifices some predictions when the input
+            // device starts to speed up, but avoids producing noisy predictions as it slows down.
+            break;
+        }
+        // TODO(b/266747654): Stop predictions if confidence is < some threshold.
 
         const TfLiteMotionPredictorSample::Point predictedPoint =
                 convertPrediction(axisFrom, axisTo, predictedR[i], predictedPhi[i]);
@@ -197,7 +208,7 @@
         coords.setAxisValue(AMOTION_EVENT_AXIS_Y, predictedPoint.y);
         coords.setAxisValue(AMOTION_EVENT_AXIS_PRESSURE, predictedPressure[i]);
 
-        predictionTime += mModel->predictionInterval();
+        predictionTime += mModel->config().predictionInterval;
         if (i == 0) {
             hasPredictions = true;
             prediction->initialize(InputEvent::nextId(), event.getDeviceId(), event.getSource(),