diff --git a/src/index.html b/src/index.html
index c198498..de72c55 100644
--- a/src/index.html
+++ b/src/index.html
@@ -151,9 +151,9 @@
             - Image is just pixels (RGB)
           </aside>
         </section>
-        <section>
-          <h2 class="r-fit-text">2. Thresholding</h2>
-          <p class="fragment">Demo 🤞</p>
+        <section data-background-image="https://docs.opencv.org/4.x/singlemarkersthresh.png">
+          <h2 class="r-fit-text text-shadow">2. Thresholding</h2>
+          <p class="fragment text-shadow">Demo 🤞</p>
           <aside class="notes" data-markdown>
             - Images aren't black and white
               - This slide is
@@ -167,6 +167,200 @@
                 - Useful in future
           </aside>
         </section>
+        <section>
+          <section>
+            <h2 class="r-fit-text">3. Edge Detection</h2>
+            <aside class="notes" data-markdown>
+              - Marker edges are straight lines
+              - Markers are squares
+                - Well, quadralaterals
+              - Filter to find hard edges
+                - Are neighbouring pixels sufficiently different from eachother?
+              - Find collections with 4 sides
+            </aside>
+          </section>
+          <section>
+            <h2 class="r-fit-text">3a. Contour Refinement</h2>
+            <aside class="notes" data-markdown>
+              - Only care about the square (ish) ones
+                - Get rid of anything else
+                - Ignore rectangles, too skewed etc
+                - Remove contours within contours
+              - Refinement is fast and simple
+                - Latter stages are more complex
+                - Exclude now whilst it's easy and cheap
+            </aside>
+          </section>
+        </section>
+        <section data-background-image="https://docs.opencv.org/4.x/singlemarkersoriginal.jpg">
+            <h2 class="r-fit-text text-shadow">4. <em>Distortion</em></h2>
+            <aside class="notes" data-markdown>
+              - Highly unlikely a marker is directly in front of you
+              - Want the simplest possible case when decoding
+                - Remove the need for special casing later
+                - Make our lives easier!
+              - Skew the image a bit
+                - Same process used for those paper scanning apps
+              - Markers are now always straight on
+            </aside>
+        </section>
+        <section data-background-image="https://docs.opencv.org/4.x/bitsextraction2.png" data-background-size="contain">
+            <h2 class="r-fit-text text-shadow">5. Bit extraction</h2>
+            <aside class="notes" data-markdown>
+              - Convert the image into some 1s and 0s
+              - Images we have are much higher resolution than the markers
+              - We know how many pixels are in a marker
+                - Divide it down into cells
+                - Add some margins in case we're slightly off
+              - Average the remaining pixels in each cell
+              - Convert into 2D list
+            </aside>
+        </section>
+        <section>
+            <h2 class="r-fit-text">6. Decoding</h2>
+            <aside class="notes" data-markdown>
+              - Just 1s and 0s now
+              - 7x7 markers have 2041 combinations
+                - There are only ~255 possible combinations
+              - Error checks
+                - Single pixel flips can be corrected
+                - Sometimes even more
+              - Try all 4 rotations
+              - Search "Hamming code" for more
+            </aside>
+        </section>
+        <section data-background-image="https://docs.opencv.org/4.x/singlemarkersdetection.jpg">
+            <h2 class="r-fit-text text-shadow">And done!</h2>
+            <p class="fragment text-shadow">...Almost</p>
+            <aside class="notes" data-markdown>
+              - And that's it
+              - We can now find markers in a given image
+              - But what if we wanted to do a little more?
+            </aside>
+        </section>
+        <section data-background-image="https://docs.opencv.org/4.x/singlemarkersaxes.jpg">
+            <h2 class="r-fit-text text-shadow">7. Pose Estimation</h2>
+            <aside class="notes" data-markdown>
+              - Now know where there's a marker
+              - Which way is it facing?
+              - We know where the corners are
+              - With some calibration, if it knows what a known-size marker looks like, it can be used to determine how far away a marker is
+              - Camera lenses have some distortion (lenses aren't completely flat), so as the image moves around the camera, it skews.
+                - If we account for that, we can get accurate angles
+              - Out the end, we get rotation and translations from the camera
+                - _complicated maths_
+                - `solvePnP` in OpenCV (entertaining name)
+                - "Perspective 'n' Point"
+                - Requires calibration for each camera model
+              - With simpler maths, can be turned into angles, distances etc
+            </aside>
+        </section>
+        <section>
+          <h2 class="r-fit-text">Another demo 🙏</h2>
+        </section>
+        <section>
+          <section>
+            <h2 class="r-fit-text">Endless possibilities 🤯</h2>
+            <aside class="notes" data-markdown>
+              - Markers are useful for lots of different purposes
+            </aside>
+          </section>
+          <section>
+            <h2 class="r-fit-text">A single marker provides:</h2>
+            <div class="columns">
+              <div class="column">
+                <ul>
+                  <li class="fragment">"id"</li>
+                  <li class="fragment">Rotation</li>
+                  <li class="fragment">Bearing</li>
+                  <li class="fragment">Distance</li>
+                </ul>
+              </div>
+              <div class="column">
+                <ul>
+                  <li class="fragment">Object tracking</li>
+                  <li class="fragment">Localization</li>
+                  <li class="fragment">Identification</li>
+                </ul>
+              </div>
+            </div>
+            <aside class="notes" data-markdown>
+              - From just a single marker
+                - id
+                - Rotation
+                - Bearing
+                - How far away it is
+              - Could be used for
+                - Tracking objects
+                - Working out where you are
+                - Working out what something is
+            </aside>
+          </section>
+          <section data-background-image="https://github.com/ju1ce/April-Tag-VR-FullBody-Tracker/raw/master/images/demo.gif"></section>
+          <section data-background-iframe="https://www.youtube-nocookie.com/embed/5iV_hB08Uns?autoplay=1"></section>
+          <section data-background-iframe="https://www.youtube-nocookie.com/embed/4sRnVUHdM4A?autoplay=1&start=17"></section>
+        </section>
+        <section>
+          <section>
+            <h2 class="r-fit-text">Don't do it yourself</h2>
+            <aside class="notes" data-markdown>
+              - I've run through this quickly
+              - Lots of intricacies
+              - OpenCV has great primitives for these operations
+                - If it's good enough for JPL on Mars, it's good enough for me
+                - (and you)
+              - OpenCV has a built-in marker detection library called ArUco
+                - Where I got lots of this from
+            </aside>
+          </section>
+          <section>
+            <h2 class="r-fit-text"><code>pip install zoloto</code></h2>
+            <pre><code data-trim data-noescape>
+              from pathlib import Path
+
+              from zoloto import MarkerType
+              from zoloto.cameras import Camera
+
+              with Camera(marker_type=MarkerType.ARUCO_6X6) as camera:
+                for frame in camera:
+                  print(
+                    "Markers I can see:",
+                    len(camera.get_visible_markers(frame=frame))
+                  )
+            </code></pre>
+            <aside class="notes" data-markdown>
+              - If you're like me
+                - Know Python
+                - Lazy
+              - I wrote a library to help
+              - Wraps OpenCV's ArUco, but with a much nicer API
+            </aside>
+          </section>
+        </section>
+        <section data-background-image="https://i.ytimg.com/vi/JICMv4TAFMA/maxresdefault.jpg">
+          <aside class="notes" data-markdown>
+            - Now you know how these markers work
+            - Makes for great geeky pub conversation
+          </aside>
+        </section>
+        <section>
+          <h2>More‽</h2>
+          <ul class="r-fit-text">
+            <li>Slides: <a href="https://slides.jakehoward.tech">slides.jakehoward.tech</a></li>
+            <li>Student Robotics: <a href="https://studentrobotics.org">studentrobotics.org</a></li>
+            <li>OpenCV: <a href="https://docs.opencv.org/4.x/d5/dae/tutorial_aruco_detection.html">opencv.org</a></li>
+            <li>AptilTag: <a href="https://april.eecs.umich.edu/software/apriltag">april.eecs.umich.edu</a></li>
+            <li>🐦 <a class="has-text-primary" href="https://twitter.com/realorangeone">@RealOrangeOne</a></li>
+          </ul>
+          <aside class="notes" data-markdown>
+            - Notes are available online
+            - Find out more about Student Robotics
+              - If your company likes sponsoring charities, let's chat
+          </aside>
+        </section>
+        <section>
+          <h1 class="is-family-code">&lt;/me&gt;</h1>
+        </section>
       </div>
     </div>
     <script type="module" src="./index.js"></script>
diff --git a/src/index.js b/src/index.js
index b4b57e2..eeaa45b 100644
--- a/src/index.js
+++ b/src/index.js
@@ -1,9 +1,10 @@
 import Reveal from 'reveal.js';
 import Markdown from 'reveal.js/plugin/markdown/markdown.js';
 import Notes from 'reveal.js/plugin/notes/notes.js';
+import Highlight from 'reveal.js/plugin/highlight/highlight.js';
 
 let deck = new Reveal({
-   plugins: [ Markdown, Notes ],
+   plugins: [ Markdown, Notes, Highlight ],
    controlsTutorial: false,
    hash: true
 })
diff --git a/src/index.scss b/src/index.scss
index b185f16..4430359 100644
--- a/src/index.scss
+++ b/src/index.scss
@@ -1,10 +1,20 @@
 $text: white;
 $text-strong: white;
 $primary: #e85537;
+$pre-background: none;
+$code-background: none;
+$code: $text;
+$family-code: var(--r-code-font);
 
 @import "../node_modules/reveal.js/css/reveal";
 @import "../node_modules/reveal.js/css/theme/source/night";
-@import "../node_modules/bulma/bulma";
+@import "../node_modules/reveal.js/plugin/highlight/monokai.css";
+
+// Bulma (the useful bits)
+@import "../node_modules/bulma/sass/utilities/_all";
+@import "../node_modules/bulma/sass/helpers/_all";
+@import "../node_modules/bulma/sass/base/_all";
+@import "../node_modules/bulma/sass/grid/_all";
 
 
 .text-shadow {