Add Blender scripts for camera views sampling and features extraction

script/Blender/Keypoints_extraction/README.md

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+# Blender keypoints extraction: an experimentation
+
+Some tests to use Blender to automatically sample camera viewpoints around an object and to extract SIFT descriptors.
+
+## Install Python OpenCV
+
+Here, Blender is directly installed from an [archive](https://www.blender.org/download/) for Linux platforms.
+
+This has the advantage to be able to use the latest version and not depend on the package manager.
+To install OpenCV (`opencv-python`), the following [script](https://github.com/luckychris/install_blender_python_modules) (credit to "luckychris") is used:
+- launch Blender from the terminal
+- switch to the `Scripting` tab
+- open and run the script (use `opencv-python` for the module to be installed)
+- in the terminal, info about the installation should be displayed
+
+With this workflow, Python OpenCV is installed locally and directly into the Blender folder.
+
+## Blender scene
+
+For these tests, a simple object is used:
+- add the Suzanne model (`Add` > `Mesh` > `Monkey`)
+- update the camera focal length and the output resolution
+
+[Triangulate](https://docs.blender.org/manual/en/4.3/modeling/meshes/editing/face/triangulate_faces.html):
+- `Edit` mode > `Face` > `Triangulate Faces` (`Ctrl T`)
+
+For the texturing:
+- `Material` > `New` > `Base Color` > `Image Texture`
+- here [`Unwrap`](https://docs.blender.org/manual/en/4.3/modeling/meshes/editing/uv.html) is used
+- `UV Editing` window > Open the image
+- move to center the mesh
+
+## Run the keypoints extraction script
+
+Switch to the `Scripting` window, open and run the [`extract_sift_sampling_Suzanne.py`](extract_sift_sampling_Suzanne.py) script.
+
+The main principles are:
+- sample equidistant camera poses around the object
+- run SIFT detector and for each feature:
+  - perform [back-face culling](https://en.wikipedia.org/wiki/Back-face_culling) for visibility test
+  - compute [ray-triangle intersection](https://docs.blender.org/api/4.3/mathutils.geometry.html#mathutils.geometry.intersect_ray_tri) to get the 3D coordinates and transform to the object frame
+  - save the list of detected features (SIFT descriptors + 3D object coordinates) into a `.npz` file format
+
+## Render a test image
+
+Move the camera, the light at the desired positions and use the [`render_still_image_Suzanne.py`](render_still_image_Suzanne.py) script to conveniently render the image and save the camera pose.
+
+## Keypoints matching and pose computation
+
+Use the [`keypoints_matching_Suzanne.py`](keypoints_matching_Suzanne.py) script.
+
+## Results
+
+### Keypoints matching
+
+A brief overview of the keypoints matching process can be seen:
+
+![keypoints matching mosaic](img_mosaic.png)
+
+Matching lines are those from the keypoints matching process, RANSAC results are not displayed.
+
+### Pose computation
+
+Running the script should give result similar to:
+
+```bash
+rvec=[[ 1.83592335 -0.06509804 -0.60995061]]
+rvec_gt=[[ 1.83833405 -0.06378919 -0.60991766]]
+
+c_T_o_est:
+[[ 0.86373993  0.25108214 -0.43693374 -0.4630725 ]
+ [-0.33764126 -0.35531447 -0.8716364  -0.11690215]
+ [-0.37410121  0.90039402 -0.2221236   5.08996118]
+ [ 0.          0.          0.          1.        ]]
+c_T_o_gt:
+[[ 0.86392033  0.25132278 -0.4364382  -0.46306577]
+ [-0.33618754 -0.35746148 -0.87132031 -0.11758688]
+ [-0.37499252  0.89947647 -0.22432667  5.09212732]
+ [ 0.          0.          0.          1.        ]]
+
+```
+
+Result with a rough simplified model should give:
+
+![pose computation](img_result.png)
+
+### Illumination change test
+
+Same camera viewpoint but with a different illumination condition:
+
+```bash
+rvec=[[ 2.3786033  -0.60075198 -0.0076497 ]]
+rvec_gt=[[ 1.83833405 -0.06378919 -0.60991766]]
+
+c_T_o_est:
+[[ 0.89370737 -0.41880363 -0.16090572 -1.16669042]
+ [-0.42276497 -0.66606072 -0.61451842 -0.50213294]
+ [ 0.15018957  0.61722495 -0.77231888  5.45509487]
+ [ 0.          0.          0.          1.        ]]
+c_T_o_gt:
+[[ 0.86392033  0.25132278 -0.4364382  -0.46306577]
+ [-0.33618754 -0.35746148 -0.87132031 -0.11758688]
+ [-0.37499252  0.89947647 -0.22432667  5.09212732]
+ [ 0.          0.          0.          1.        ]]
+```
+
+![Illumination chage](img_result_compare.png)