Reorganizing gaze analizis pipeline documentation.

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-Visualize heatmap
-=================
-
-Heatmap is an optional [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) pipeline step. It is executed at each new gaze position to update heatmap image.
-
-![Heatmap](../../img/ar_frame_heatmap.png)
-
-## Enable ArFrame heatmap
-
-[ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) heatmap visualization can be enabled thanks to a dedicated JSON entry.
-
-Here is the JSON ArFrame configuration file example where heatmap visualization is enabled:
-
-```json
-{
-    "name": "My FullHD screen",
-    "size": [1920, 1080],
-    ...
-    "heatmap": {
-        "size": [320, 180],
-        "sigma": 0.025,
-        "buffer": 0
-    }
-}
-```
-
-Then, here is how to access to heatmap object:
-
-```python
-
-# Assuming an ArFrame is loaded
-...
-
-print("heatmap:", ar_frame.heatmap)
-```
-
-Finally, here is what the program writes in console:
-
-```txt
-heatmap: Heatmap(size=[320, 180], buffer=0, sigma=0.025)
-```
-
-Now, let's understand the meaning of each JSON entry.
-
-### Size
-
-The heatmap image size in pixel. Higher size implies higher CPU load.
-
-### Sigma
-
-The gaussian point spreading to draw at each gaze position.
-
-![Point spread](../../img/point_spread.png)
-
-### Buffer 
-
-The size of point spread images buffer (0 means no buffering) to visualize only last N gaze positions.
-
-## Export heatmap to PNG file
-
-Once timestamped gaze positions have been processed by [ArFrame.look](../../argaze.md/#argaze.ArFeatures.ArFrame.look) method, it is possible to write heatmap image thanks to OpenCV package.
-
-```python
-import cv2
-
-# Assuming that timestamped gaze positions have been processed by ArFrame.look method
-...
-
-# Export heatmap image
-cv2.imwrite('./heatmap.png', ar_frame.heatmap.image)
-```
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