Bug fix in Kalman Filter process covariance matrix.

examples/example_scripts/mot_Caffe_SSDMobileNet.py

@@ -57,7 +57,7 @@ def main(video_path, model, tracker):
         '--gpu', type=bool, default=False, help='Flag to use gpu to run the deep learning model. Default is `False`')
 
     parser.add_argument(
-        '--tracker', type=str, default='IOUTracker', help="Tracker used to track objects."
+        '--tracker', type=str, default='SORT', help="Tracker used to track objects."
         " Options include ['CentroidTracker', 'CentroidKF_Tracker', 'SORT', IOUTracker]")
 
     args = parser.parse_args()
@@ -81,7 +81,7 @@ def main(video_path, model, tracker):
         confidence_threshold=0.5,
         nms_threshold=0.2,
         draw_bboxes=True,
-        use_gpu=args.gpuq
+        use_gpu=args.gpu
     )
 
     main(args.video, model, tracker)

motrackers/kalman_tracker.py

@@ -101,10 +101,16 @@ def update(self, z):
 
 
 def get_process_covariance_matrix(dt):
+    # a = np.array([
+    #     [0.25 * dt ** 4, 0.5 * dt ** 3, 0.5 * dt ** 2],
+    #     [0.5 * dt ** 3, dt ** 2, dt],
+    #     [0.5 * dt ** 2, dt, 1]
+    # ])
+
     a = np.array([
-        [0.25 * dt ** 4, 0.5 * dt ** 3, 0.5 * dt ** 2],
-        [0.5 * dt ** 3, dt ** 2, dt],
-        [0.5 * dt ** 2, dt, 1]
+        [dt ** 6 / 36., dt ** 5 / 24., dt ** 4 / 6.],
+        [dt ** 5 / 24., 0.25 * dt ** 4, 0.5 * dt ** 3],
+        [dt ** 4 / 6., 0.5 * dt ** 3, dt ** 2]
     ])
     return a