diff --git a/app.py b/app.py
index fb94638..bd4fc0b 100644
--- a/app.py
+++ b/app.py
@@ -177,6 +177,9 @@ def get_frame_data():
         
         frame_data['new_point_cloud'] = sampled_point_cloud.tolist()
         frame_data['combined_point_cloud'] = combined_point_cloud.tolist()
+        new_added_pts = ReconstructionUtil.get_new_added_points(combined_point_cloud, sampled_point_cloud)
+        frame_data["new_added_pts"] = new_added_pts.tolist()
+
         combined_point_cloud = np.concatenate([combined_point_cloud, sampled_point_cloud], axis=0)
         
         combined_point_cloud = PtsUtil.voxel_downsample_point_cloud(combined_point_cloud, 0.01)
@@ -218,6 +221,8 @@ def parse_to_frame_data(inference_result):
         coverage_rate = inference_result["coverage_rate_seq"][idx]
         frame_data['new_point_cloud'] = target_pts.tolist()
         frame_data['combined_point_cloud'] = combined_point_cloud.tolist()
+        new_added_pts = ReconstructionUtil.get_new_added_points(combined_point_cloud, target_pts)
+        frame_data["new_added_pts"] = new_added_pts.tolist()
         combined_point_cloud = np.concatenate([combined_point_cloud, target_pts], axis=0)
         frame_data["coverage_rate"] = float(coverage_rate)
         delta_CR = frame_data["coverage_rate"] - last_CR
diff --git a/pts.py b/pts.py
index c15554a..03bbf88 100644
--- a/pts.py
+++ b/pts.py
@@ -19,6 +19,8 @@ class PtsUtil:
     
     @staticmethod
     def random_downsample_point_cloud(point_cloud, num_points):
+        if point_cloud.shape[0] == 0:
+            return point_cloud
         idx = np.random.choice(len(point_cloud), num_points, replace=True)
         return point_cloud[idx]
     
diff --git a/reconstruction.py b/reconstruction.py
index 8082370..7b45127 100644
--- a/reconstruction.py
+++ b/reconstruction.py
@@ -31,6 +31,18 @@ class ReconstructionUtil:
         
         return filtered_sampled_points[:, :3]
     
+    @staticmethod
+    def get_new_added_points(old_combined_pts, new_pts, threshold=0.005):
+        if old_combined_pts.size == 0:
+            return new_pts
+        if new_pts.size == 0:
+            return np.array([])
+
+        tree = cKDTree(old_combined_pts)
+        distances, _ = tree.query(new_pts, k=1)
+        new_added_points = new_pts[distances > threshold]
+        return new_added_points
+    
 if __name__ == "__main__":
     import os
     root = "/media/hofee/data/project/python/nbv_reconstruction/nbv_rec_visualize/data/sample/"