diff --git a/pose_anonymization/data/__init__.py b/pose_anonymization/data/__init__.py
index ae33f6a..92e22c0 100644
--- a/pose_anonymization/data/__init__.py
+++ b/pose_anonymization/data/__init__.py
@@ -2,7 +2,8 @@
 from pathlib import Path
 
 import numpy as np
-from pose_format import PoseHeader
+from pose_format import PoseHeader, Pose
+from pose_format.numpy import NumPyPoseBody
 from pose_format.utils.reader import BufferReader
 
 CURRENT_DIR = Path(__file__).parent
@@ -31,3 +32,11 @@ def load_mean_and_std():
     std[std == 0] = 1
 
     return np.array(mean), std
+
+@lru_cache(maxsize=1)
+def load_mean_and_std_pose():
+    pose_header = load_pose_header()
+    mean, std = load_mean_and_std()
+    mean_body = NumPyPoseBody(fps=1, data=mean.reshape((1, 1, -1, 3)), confidence=np.ones((1, 1, len(mean))))
+    std_body = NumPyPoseBody(fps=1, data=std.reshape((1, 1, -1, 3)), confidence=np.ones((1, 1, len(std))))
+    return Pose(header=pose_header, body=mean_body), Pose(header=pose_header, body=std_body)
diff --git a/pose_anonymization/data/calc_mean_std.py b/pose_anonymization/data/calc_mean_std.py
new file mode 100644
index 0000000..bf62c71
--- /dev/null
+++ b/pose_anonymization/data/calc_mean_std.py
@@ -0,0 +1,90 @@
+from functools import partial
+from pathlib import Path
+
+import numpy as np
+from pose_format import Pose, PoseHeader
+from tqdm.contrib.concurrent import process_map
+
+from pose_anonymization.data.normalization import pre_process_pose
+
+CURRENT_DIR = Path(__file__).parent
+
+
+def process_file(file, pose_header: PoseHeader):
+    with open(file, 'rb') as pose_file:
+        pose = Pose.read(pose_file.read())
+        pose = pre_process_pose(pose, pose_header=pose_header)
+    tensor = pose.body.data.filled(0)
+
+    frames_sum = np.sum(tensor, axis=(0, 1))
+    frames_squared_sum = np.sum(np.square(tensor), axis=(0, 1))
+    unmasked_frames = pose.body.data[:, :, :, 0:1].mask == False
+    num_unmasked_frames = np.sum(unmasked_frames, axis=(0, 1))
+
+    return frames_sum, frames_squared_sum, num_unmasked_frames
+
+
+def calc_mean_and_std(files, pose_header: PoseHeader):
+    cumulative_sum, squared_sum, frames_count = None, None, None
+
+    process_func = partial(process_file, pose_header=pose_header)
+    results = process_map(process_func, files, max_workers=None, chunksize=1)
+
+    for frames_sum, frames_squared_sum, num_unmasked_frames in results:
+        cumulative_sum = frames_sum if cumulative_sum is None else cumulative_sum + frames_sum
+        squared_sum = frames_squared_sum if squared_sum is None else squared_sum + frames_squared_sum
+        frames_count = num_unmasked_frames if frames_count is None else frames_count + num_unmasked_frames
+
+    mean = cumulative_sum / frames_count
+    std = np.sqrt((squared_sum / frames_count) - np.square(mean))
+
+    return mean, std
+
+
+def main(poses_location: str):
+    print("Listing files...")
+    files = list(Path(poses_location).glob("*.pose"))
+    print(f"Processing {len(files)} files")
+
+    # get a single random pose
+    with open(files[0], 'rb') as pose_file:
+        pose = Pose.read(pose_file.read())
+        pose = pre_process_pose(pose)
+
+    mean, std = calc_mean_and_std(files, pose.header)
+
+    # store header
+    with open(CURRENT_DIR / "header.poseheader", "wb") as f:
+        pose.header.write(f)
+
+    i = 0
+    mean_std_info = {}
+    for component in pose.header.components:
+        component_info = {}
+        for point in component.points:
+            component_info[point] = {
+                "mean": mean[i].tolist(),
+                "std": std[i].tolist()
+            }
+            i += 1
+        mean_std_info[component.name] = component_info
+
+    import json
+
+    with open(CURRENT_DIR / "pose_normalization.json", "w", encoding="utf-8") as f:
+        json.dump(mean_std_info, f, indent=2)
+
+
+if __name__ == "__main__":
+    import argparse
+
+    parser = argparse.ArgumentParser(description='Collect normalization info')
+    parser.add_argument('--dir', type=str, help='Directory containing the pose files',
+                        default="/Volumes/Echo/GCS/sign-mt-poses")
+
+    args = parser.parse_args()
+
+    if not Path(args.dir).exists():
+        raise FileNotFoundError(f"Directory {args.dir} does not exist")
+
+    main(args.dir)
diff --git a/pose_anonymization/data/draw_mean_pose.py b/pose_anonymization/data/draw_mean_pose.py
new file mode 100644
index 0000000..a160491
--- /dev/null
+++ b/pose_anonymization/data/draw_mean_pose.py
@@ -0,0 +1,25 @@
+from pathlib import Path
+
+import cv2
+from pose_format.pose_visualizer import PoseVisualizer
+from pose_format.utils.generic import reduce_holistic
+
+from pose_anonymization.appearance import normalize_pose_size
+from pose_anonymization.data import load_mean_and_std_pose
+from pose_anonymization.data.normalization import unshift_hands
+
+if __name__ == "__main__":
+    mean_pose, _ = load_mean_and_std_pose()
+    unshift_hands(mean_pose)
+    normalize_pose_size(mean_pose)
+
+    poses = {
+        "full": mean_pose,
+        "reduced": reduce_holistic(mean_pose)
+    }
+    for name, pose in poses.items():
+        pose.focus()
+
+        v = PoseVisualizer(pose)
+        image_path = Path(__file__).parent / f"mean_pose_{name}.png"
+        cv2.imwrite(str(image_path), next(v.draw()))
diff --git a/pose_anonymization/data/header.poseheader b/pose_anonymization/data/header.poseheader
index 82a8df7..50a5104 100644
Binary files a/pose_anonymization/data/header.poseheader and b/pose_anonymization/data/header.poseheader differ
diff --git a/pose_anonymization/data/normalization.py b/pose_anonymization/data/normalization.py
new file mode 100644
index 0000000..c9526e3
--- /dev/null
+++ b/pose_anonymization/data/normalization.py
@@ -0,0 +1,76 @@
+from pose_format import Pose, PoseHeader
+from pose_format.utils.generic import pose_normalization_info, correct_wrists, hands_components
+
+from pose_anonymization.data import load_mean_and_std, load_mean_and_std_pose
+
+
+def shift_hand(pose: Pose, hand_component: str, wrist_name: str):
+    # pylint: disable=protected-access
+    wrist_index = pose.header._get_point_index(hand_component, wrist_name)
+    hand = pose.body.data[:, :, wrist_index: wrist_index + 21]
+    wrist = hand[:, :, 0:1]
+    pose.body.data[:, :, wrist_index: wrist_index + 21] = hand - wrist
+
+
+def shift_hands(pose: Pose):
+    (left_hand_component, right_hand_component), _, (wrist, _) = hands_components(pose.header)
+    shift_hand(pose, left_hand_component, wrist)
+    shift_hand(pose, right_hand_component, wrist)
+
+
+def unshift_hand(pose: Pose, hand_component: str):
+    # pylint: disable=protected-access
+    wrist_index = pose.header._get_point_index(hand_component, "WRIST")
+    hand = pose.body.data[:, :, wrist_index: wrist_index + 21]
+    body_wrist_name = "LEFT_WRIST" if hand_component == "LEFT_HAND_LANDMARKS" else "RIGHT_WRIST"
+    # pylint: disable=protected-access
+    body_wrist_index = pose.header._get_point_index("POSE_LANDMARKS", body_wrist_name)
+    body_wrist = pose.body.data[:, :, body_wrist_index: body_wrist_index + 1]
+    pose.body.data[:, :, wrist_index: wrist_index + 21] = hand + body_wrist
+
+
+def unshift_hands(pose: Pose):
+    (left_hand_component, right_hand_component), _, _ = hands_components(pose.header)
+    unshift_hand(pose, left_hand_component)
+    unshift_hand(pose, right_hand_component)
+
+
+def pose_like(pose: Pose, pose_header: PoseHeader):
+    component_names = [component.name for component in pose_header.components]
+    component_points = {component.name: component.points for component in pose.header.components}
+    return pose.get_components(component_names, component_points)
+
+
+def pre_process_pose(pose: Pose, pose_header: PoseHeader = None):
+    if pose_header is not None:
+        pose = pose_like(pose, pose_header)
+
+    # Align hand wrists with body wrists
+    correct_wrists(pose)
+    # Adjust pose based on shoulder positions
+    pose = pose.normalize(pose_normalization_info(pose.header))
+    # Shift hands to origin
+    shift_hands(pose)
+    return pose
+
+
+def load_mean_and_std_for_pose(pose: Pose):
+    mean_pose, std_pose = load_mean_and_std_pose()
+    mean_pose = pose_like(mean_pose, pose.header)
+    std_pose = pose_like(std_pose, pose.header)
+    return (mean_pose.body.data.reshape((-1, 3)),
+            std_pose.body.data.reshape((-1, 3)))
+
+
+def normalize_mean_std(pose: Pose):
+    pose = pre_process_pose(pose)
+    mean, std = load_mean_and_std_for_pose(pose)
+    pose.body.data = (pose.body.data - mean) / std
+    return pose
+
+
+def unnormalize_mean_std(pose: Pose):
+    mean, std = load_mean_and_std()
+    pose.body.data = (pose.body.data * std) + mean
+    unshift_hands(pose)
+    return pose
diff --git a/pose_anonymization/data/pose_normalization.json b/pose_anonymization/data/pose_normalization.json
index 195dd14..40fcce8 100644
--- a/pose_anonymization/data/pose_normalization.json
+++ b/pose_anonymization/data/pose_normalization.json
@@ -2,6016 +2,6136 @@
   "POSE_LANDMARKS": {
     "NOSE": {
       "mean": [
-        -0.020603645839070907,
-        -0.5959755786569082,
-        -0.0052701341149911105
+        -0.018512987444908098,
+        -0.5896256647634406,
+        -0.005184799778270476
       ],
       "std": [
-        0.06115204970429412,
-        0.058710006235356646,
-        0.001872998374262429
+        0.09468899115690094,
+        0.0685381497689286,
+        0.0028078065387853214
       ]
     },
     "LEFT_EYE_INNER": {
       "mean": [
-        0.04675994741948999,
-        -0.6930163358392426,
-        -0.0048220657077106335
+        0.045109903893630024,
+        -0.6874672857155111,
+        -0.004760198801872015
       ],
       "std": [
-        0.060482108052021276,
-        0.05566482597579087,
-        0.0018341759037067088
+        0.08778472026335826,
+        0.06834006023807311,
+        0.002732944945154693
       ]
     },
     "LEFT_EYE": {
       "mean": [
-        0.08721219738375596,
-        -0.6919683657544232,
-        -0.0048234587617681955
+        0.08836309014567723,
+        -0.6844766609887415,
+        -0.004766744104205352
       ],
       "std": [
-        0.05889441901140183,
-        0.054839086410791264,
-        0.0018348959000093793
+        0.08540771458745255,
+        0.06800847203964198,
+        0.0027343949202323138
       ]
     },
     "LEFT_EYE_OUTER": {
       "mean": [
-        0.1225524157811048,
-        -0.6897160785200276,
-        -0.004822271511936329
+        0.12779325550377252,
+        -0.6808482666677502,
+        -0.004767292916378294
       ],
       "std": [
-        0.05870850877131256,
-        0.054250065607486235,
-        0.0018355833112775836
+        0.08435341150842522,
+        0.06795476446019634,
+        0.0027344045565626716
       ]
     },
     "RIGHT_EYE_INNER": {
       "mean": [
-        -0.08432988621696963,
-        -0.689762948427843,
-        -0.004848048892121962
+        -0.07902023962860681,
+        -0.6887397549417738,
+        -0.004729518931659181
       ],
       "std": [
-        0.061737469468520996,
-        0.05665377645453432,
-        0.00185877948301446
+        0.0860253702660086,
+        0.06842120583254484,
+        0.0027355165143081077
       ]
     },
     "RIGHT_EYE": {
       "mean": [
-        -0.12813642646443316,
-        -0.6864761704835763,
-        -0.004847958017528798
+        -0.1176615827190023,
+        -0.6862178111079358,
+        -0.004738037982655616
       ],
       "std": [
-        0.060835292051211444,
-        0.05608480312749338,
-        0.001859371953498622
+        0.08352946936263698,
+        0.06816260059201544,
+        0.0027374917390461996
       ]
     },
     "RIGHT_EYE_OUTER": {
       "mean": [
-        -0.16700901085951816,
-        -0.6820083392855836,
-        -0.004852446687874673
+        -0.15472440844161345,
+        -0.6831580821344303,
+        -0.004745134918818311
       ],
       "std": [
-        0.05957318007137157,
-        0.05549792370307076,
-        0.0018599158082745607
+        0.08117624758127878,
+        0.06832462572810555,
+        0.002739083930343505
       ]
     },
     "LEFT_EAR": {
       "mean": [
-        0.18478113908381716,
-        -0.6298677221724291,
-        -0.0017399032692769945
+        0.17558791656866113,
+        -0.6287317459522022,
+        -0.002002539904617479
       ],
       "std": [
-        0.057733898275172585,
-        0.04792559707710173,
-        0.0014629323119980326
+        0.0708250031973409,
+        0.06159792458713847,
+        0.002162375932115164
       ]
     },
     "RIGHT_EAR": {
       "mean": [
-        -0.21337732513230828,
-        -0.620192678427752,
-        -0.0017811054089002603
+        -0.20530156885601622,
+        -0.6307414274692089,
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       "std": [
-        0.056015326723367745,
-        0.047936689458151764,
-        0.0015833132436399156
+        0.06705101450362821,
+        0.06236792270592483,
+        0.002180097382564324
       ]
     },
     "MOUTH_LEFT": {
       "mean": [
-        0.06305335143446893,
-        -0.478569572835871,
-        -0.004119872113489358
+        0.06072465328614621,
+        -0.4806773420086853,
+        -0.0040590849022119225
       ],
       "std": [
-        0.05585149462804898,
-        0.05071679681206075,
-        0.0016814448094725342
+        0.08709217550124386,
+        0.06110532334219883,
+        0.002524872143208484
       ]
     },
     "MOUTH_RIGHT": {
       "mean": [
-        -0.1018885425381362,
-        -0.47549312787937753,
-        -0.004137715874413553
+        -0.08725356969634313,
+        -0.4834167715946633,
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       "std": [
-        0.0583708470581484,
-        0.051591789609106625,
-        0.0017115422429244552
+        0.0859810217629468,
+        0.06298507710723125,
+        0.0025375139059945584
       ]
     },
     "LEFT_SHOULDER": {
       "mean": [
-        0.49811733501672706,
-        0.003251094164313307,
-        0.00014758683750005388
+        0.4980923345301671,
+        0.006731708010328918,
+        -6.206472099395518e-05
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       "std": [
-        0.06389513143077369,
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-        0.0010677143878379286
+        0.06720085282451047,
+        0.041737651598926825,
+        0.0017139016530118515
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     },
     "RIGHT_SHOULDER": {
       "mean": [
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-        -0.003251086947801497,
-        -0.00014758693772938457
+        -0.498092394725504,
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       "std": [
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-        0.044425124044468446,
-        0.0011664361081301436
+        0.0720796081450892,
+        0.04152661170283864,
+        0.0017006318377804051
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     },
     "LEFT_ELBOW": {
       "mean": [
-        0.7170714778410365,
-        0.7945037814436355,
-        -0.0007108759265830106
+        0.7070742312340661,
+        0.8039176931100267,
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       "std": [
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-        0.13082184452195603,
-        0.0018681716684588656
+        0.14247701812535135,
+        0.14183549328126704,
+        0.001846729714782859
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     },
     "RIGHT_ELBOW": {
       "mean": [
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-        0.7592151883681069,
-        -0.001824716393437912
+        -0.7544891349674261,
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       "std": [
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+        0.15278708892624704,
+        0.16998071276052903,
+        0.0018929154328605118
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     },
     "LEFT_WRIST": {
       "mean": [
-        0.499245873446733,
-        0.9622243596116599,
-        -0.0005711651265939105
+        0.45291179140871085,
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       "std": [
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     "RIGHT_WRIST": {
       "mean": [
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+        -0.4887613951653814,
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       "std": [
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     },
     "LEFT_PINKY": {
       "mean": [
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       "std": [
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     "RIGHT_PINKY": {
       "mean": [
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+        -0.43143912152129266,
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       "std": [
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     },
     "LEFT_INDEX": {
       "mean": [
-        0.42694421680418254,
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       "std": [
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     },
     "RIGHT_INDEX": {
       "mean": [
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+        -0.3870117123571847,
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       "std": [
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+        0.7632050669647809,
+        0.0037287340776391165
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     },
     "LEFT_THUMB": {
       "mean": [
-        0.4091361492819564,
-        0.9613677692818182,
-        -0.004739863223516569
+        0.35661333811284307,
+        0.9566614943823454,
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       "std": [
-        0.2713579504284436,
-        0.6599371401428087,
-        0.003280141017544523
+        0.28332283026565525,
+        0.6635976000904447,
+        0.003340682227150601
       ]
     },
     "RIGHT_THUMB": {
       "mean": [
-        -0.4091060430637976,
-        0.6998202727199141,
-        -0.006782587765955081
+        -0.378465840575961,
+        0.6708589709035305,
+        -0.004808682383518637
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       "std": [
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+    "RIGHT_FOOT_INDEX": {
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diff --git a/pyproject.toml b/pyproject.toml
index 86bd481..41984d9 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -33,7 +33,7 @@ disable = [
 [tool.setuptools]
 packages = [
     "pose_anonymization",
-    "pose_anonymization.data"
+    "pose_anonymization.data",
 ]
 
 [tool.setuptools.package-data]