fix: revise the filtering process flow

Signed-off-by: Taekjin LEE <taekjin.lee@tier4.jp>

perception/multi_object_tracker/src/tracker/model/tracker_base.cpp

@@ -58,30 +58,36 @@ void Tracker::updateClassification(
   const std::vector<autoware_auto_perception_msgs::msg::ObjectClassification> & classification)
 {
   // classification algorithm:
-  // 0. Remove the class with probability < 0.005
-  // 1. Decay all existing probability
-  // 2. Update the matched classification probability with a gain
-  // 3. If the label is not found, add it to the classification list
-  // 4. Normalize
+  // 0. Normalize the input classification
+  // 1-1. Update the matched classification probability with a gain (ratio of 0.05)
+  // 1-2. If the label is not found, add it to the classification list
+  // 2. Remove the class with probability < remove_threshold (0.001)
+  // 3. Normalize tracking classification
 
-  // Gain and decay
+  // Parameters
+  // if the remove_threshold is too high (compare to the gain), the classification will be removed
+  // immediately
   const double gain = 0.05;
-  const double decay = 1.0 - gain;
+  constexpr double remove_threshold = 0.001;
 
-  // If the probability is less than 0.005, remove the class
-  classification_.erase(
-    std::remove_if(
-      classification_.begin(), classification_.end(),
-      [](const auto & class_) { return class_.probability < 0.005; }),
-    classification_.end());
+  // Normalization function
+  auto normalizeProbabilities =
+    [](std::vector<autoware_auto_perception_msgs::msg::ObjectClassification> & classification) {
+      double sum = 0.0;
+      for (const auto & class_ : classification) {
+        sum += class_.probability;
+      }
+      for (auto & class_ : classification) {
+        class_.probability /= sum;
+      }
+    };
 
-  // Decay all existing probability
-  for (auto & class_ : classification_) {
-    class_.probability *= decay;
-  }
+  // Normalize the input
+  auto classification_input = classification;
+  normalizeProbabilities(classification_input);
 
   // Update the matched classification probability with a gain
-  for (const auto & new_class : classification) {
+  for (const auto & new_class : classification_input) {
     bool found = false;
     for (auto & old_class : classification_) {
       if (new_class.label == old_class.label) {
@@ -98,14 +104,15 @@ void Tracker::updateClassification(
     }
   }
 
-  // Normalize
-  double sum = 0.0;
-  for (const auto & class_ : classification_) {
-    sum += class_.probability;
-  }
-  for (auto & class_ : classification_) {
-    class_.probability /= sum;
-  }
+  // If the probability is less than the threshold, remove the class
+  classification_.erase(
+    std::remove_if(
+      classification_.begin(), classification_.end(),
+      [remove_threshold](const auto & class_) { return class_.probability < remove_threshold; }),
+    classification_.end());
+
+  // Normalize tracking classification
+  normalizeProbabilities(classification_);
 }
 
 geometry_msgs::msg::PoseWithCovariance Tracker::getPoseWithCovariance(