diff --git a/camdetect.py b/camdetect.py
index 1791514..a8910af 100755
--- a/camdetect.py
+++ b/camdetect.py
@@ -9,7 +9,6 @@ import json
 import numpy as np
 import os
 import signal
-import socket
 import sys
 from datetime import datetime, timedelta
 from jpeg2dct.numpy import loads
@@ -107,7 +106,7 @@ gauge_download_queue_size.set(0)
 assert SLIDE_WINDOW <= 8  # This is 256 frames which should be enough
 
 
-async def upload(bucket, blob: bytes, event_id):
+async def upload(bucket, blob: bytes, thumb: bytes, event_id):
     """
     Upload single JPEG blob to S3 bucket
     """
@@ -115,6 +114,11 @@ async def upload(bucket, blob: bytes, event_id):
     # Generate S3 path based on the JPEG blob SHA512 digest
     fp = hashlib.sha512(blob).hexdigest()
     path = "%s/%s/%s/%s.jpg" % (fp[:4], fp[4:8], fp[8:12], fp[12:])
+
+    # First upload the thumbnail
+    await bucket.upload_fileobj(io.BytesIO(thumb), "thumb/%s" % path)
+
+    # Proceed to upload the original JPEG frame
     await bucket.upload_fileobj(io.BytesIO(blob), path)
 
     # Add screenshot path to the event
@@ -139,8 +143,8 @@ async def uploader(queue):
     async with session.resource("s3", endpoint_url=S3_ENDPOINT_URL) as s3:
         bucket = await s3.Bucket(S3_BUCKET_NAME)
         while True:
-            blob, event_id = await queue.get()
-            await upload(bucket, blob, event_id)
+            blob, thumb, event_id = await queue.get()
+            await upload(bucket, blob, thumb, event_id)
             counter_uploaded_frames.inc()
             gauge_upload_queue_size.set(queue.qsize())
 
@@ -188,13 +192,16 @@ async def motion_detector(reference_frame, download_queue, upload_queue):
     event_id = None
     differing_blocks = []
     while True:
-        dt, blob, y = await download_queue.get()
-        app.ctx.last_frame = blob
+        dt, blob, dct, thumb = await download_queue.get()
+        app.ctx.last_frame, app.ctx.dct = blob, dct
 
         # Signal /bypass and /debug handlers about new frame
         app.ctx.event_frame.set()
         app.ctx.event_frame.clear()
 
+        # Separate most significant luma value for each DCT (8x8 pixel) block
+        y = np.int16(dct[0][:, :, 0])
+
         # Update metrics
         gauge_total_blocks.set(y.shape[0] * y.shape[1])
         gauge_last_frame.set(dt.timestamp())
@@ -246,7 +253,7 @@ async def motion_detector(reference_frame, download_queue, upload_queue):
             counter_movement_frames.inc()
             try:
                 # Push JPEG blob into upload queue
-                upload_queue.put_nowait((blob, event_id))
+                upload_queue.put_nowait((blob, thumb, event_id))
             except asyncio.QueueFull:
                 counter_upload_dropped_frames.inc()
             gauge_upload_queue_size.set(upload_queue.qsize())
@@ -264,6 +271,41 @@ async def motion_detector(reference_frame, download_queue, upload_queue):
             gauge_event_active.set(0)
 
 
+def generate_thumbnail(dct):
+    """
+    This is highly efficient and highly inaccurate function to generate
+    thumbnail based purely on JPEG coefficients
+    """
+    y, cr, cb = dct
+
+    # Determine aspect ratio and minimum dimension for cropping
+    ar = y.shape[0] < y.shape[1]
+    dm = (y.shape[0] if ar else y.shape[1]) & 0xfffffff8
+
+    # Determine cropping slices to make it square
+    jl = ((y.shape[1] >> 1) - (dm >> 1) if ar else 0)
+    jt = (0 if ar else (y.shape[0] >> 1) - (dm >> 1))
+    jr = jl + dm
+    jb = jt + dm
+
+    # Do the actual crop
+    ty = y[jt:jb, jl:jr, 0]
+    tb = cb[jt >> 1:jb >> 1, jl >> 1:jr >> 1, 0]
+    tr = cr[jt >> 1:jb >> 1, jl >> 1:jr >> 1, 0]
+
+    # Upsample chroma, dummy convert first coeff and stack all channels
+    m = np.dstack((
+        np.array((ty >> 3) + 127, dtype=np.uint8),
+        np.array(
+            (tb.repeat(2, 1).repeat(2, 0) >> 3) + 127, dtype=np.uint8)[:dm],
+        np.array(
+            (tr.repeat(2, 1).repeat(2, 0) >> 3) + 127, dtype=np.uint8)[:dm]))
+    _, jpeg = cv2.imencode(".jpg",
+                           cv2.cvtColor(m, cv2.COLOR_YCrCb2RGB),
+                           (cv2.IMWRITE_JPEG_QUALITY, 80))
+    return jpeg
+
+
 async def download(resp, queue):
     """
     This coroutine iterates over HTTP connection chunks
@@ -286,15 +328,16 @@ async def download(resp, queue):
                 # Assemble JPEG blob
                 blob = buf + data[:marker+2]
 
-                # Parse DCT coeffs and keep DCT coeffs only for Y channel
-                y, _, _ = loads(blob)
+                # Parse DCT coefficients
+                dct = loads(blob)
 
                 try:
                     # Convert Y component to 16 bit for easier handling
                     queue.put_nowait((
                         datetime.utcnow(),
                         blob,
-                        np.int16(y[:, :, 0])))
+                        dct,
+                        generate_thumbnail(dct)))
                 except asyncio.QueueFull:
                     counter_download_dropped_frames.inc()
                 data = data[marker+2:]