diff --git a/frigate/mqtt.py b/frigate/mqtt.py
index f6a9e57a4..155c28580 100644
--- a/frigate/mqtt.py
+++ b/frigate/mqtt.py
@@ -3,13 +3,14 @@ import cv2
 import threading
 
 class MqttObjectPublisher(threading.Thread):
-    def __init__(self, client, topic_prefix, objects_parsed, detected_objects, best_person_frame):
+    def __init__(self, client, topic_prefix, objects_parsed, detected_objects, best_person_frame, label):
         threading.Thread.__init__(self)
         self.client = client
         self.topic_prefix = topic_prefix
         self.objects_parsed = objects_parsed
         self._detected_objects = detected_objects
         self.best_person_frame = best_person_frame
+        self.label = label
 
     def run(self):
         last_sent_payload = ""
@@ -24,7 +25,7 @@ class MqttObjectPublisher(threading.Thread):
 
             # add all the person scores in detected objects
             detected_objects = self._detected_objects.copy()
-            person_score = sum([obj['score'] for obj in detected_objects if obj['name'] == 'person'])
+            person_score = sum([obj['score'] for obj in detected_objects if obj['name'] == self.label])
             # if the person score is more than 100, set person to ON
             payload['person'] = 'ON' if int(person_score*100) > 100 else 'OFF'
 
diff --git a/frigate/objects.py b/frigate/objects.py
index 1ae63b3f3..0a7043a26 100644
--- a/frigate/objects.py
+++ b/frigate/objects.py
@@ -38,11 +38,12 @@ class ObjectCleaner(threading.Thread):
 # Maintains the frame and person with the highest score from the most recent
 # motion event
 class BestPersonFrame(threading.Thread):
-    def __init__(self, objects_parsed, recent_frames, detected_objects):
+    def __init__(self, objects_parsed, recent_frames, detected_objects, label):
         threading.Thread.__init__(self)
         self.objects_parsed = objects_parsed
         self.recent_frames = recent_frames
         self.detected_objects = detected_objects
+        self.label = label
         self.best_person = None
         self.best_frame = None
 
@@ -55,7 +56,7 @@ class BestPersonFrame(threading.Thread):
 
             # make a copy of detected objects
             detected_objects = self.detected_objects.copy()
-            detected_people = [obj for obj in detected_objects if obj['name'] == 'person']
+            detected_people = [obj for obj in detected_objects if obj['name'] == self.label]
 
             # get the highest scoring person
             new_best_person = max(detected_people, key=lambda x:x['score'], default=self.best_person)
diff --git a/frigate/video.py b/frigate/video.py
index 7a1d7ae70..54c7c532f 100644
--- a/frigate/video.py
+++ b/frigate/video.py
@@ -130,6 +130,7 @@ class Camera:
         self.frame_size = self.frame_shape[0] * self.frame_shape[1] * self.frame_shape[2]
         self.mqtt_client = mqtt_client
         self.mqtt_topic_prefix = '{}/{}'.format(mqtt_prefix, self.name)
+        self.label = config.get('label', 'person')
 
         # create a numpy array for the current frame in initialize to zeros
         self.current_frame = np.zeros(self.frame_shape, np.uint8)
@@ -170,7 +171,7 @@ class Camera:
         self.frame_tracker.start()
 
         # start a thread to store the highest scoring recent person frame
-        self.best_person_frame = BestPersonFrame(self.objects_parsed, self.recent_frames, self.detected_objects)
+        self.best_person_frame = BestPersonFrame(self.objects_parsed, self.recent_frames, self.detected_objects, self.label)
         self.best_person_frame.start()
 
         # start a thread to expire objects from the detected objects list
@@ -178,7 +179,7 @@ class Camera:
         self.object_cleaner.start()
 
         # start a thread to publish object scores (currently only person)
-        mqtt_publisher = MqttObjectPublisher(self.mqtt_client, self.mqtt_topic_prefix, self.objects_parsed, self.detected_objects, self.best_person_frame)
+        mqtt_publisher = MqttObjectPublisher(self.mqtt_client, self.mqtt_topic_prefix, self.objects_parsed, self.detected_objects, self.best_person_frame, self.label)
         mqtt_publisher.start()
 
         # create a watchdog thread for capture process
@@ -255,7 +256,7 @@ class Camera:
             # Store object area to use in bounding box labels
             obj['area'] = (obj['xmax']-obj['xmin'])*(obj['ymax']-obj['ymin'])
 
-            if obj['name'] == 'person':
+            if obj['name'] == self.label:
                 # find the matching region
                 region = None
                 for r in self.regions: