P1p3l1n3 /// TØØl5
In 2016 a bunch of friends and colleagues from work decided to embark in the producion of a teaser for what would become a bigger film the followin years. I was in charge of developing from zero a pipeline that would integrate Tactic as Digital Asset Management System, Maya + Yeti + Arnold + AlShaders.
These videos showcase the two main tools developped for each department: they handle the chek-in and check-out of assets, so, the inputs and outputs of every department in the pipeline. We finished the teaser before the pipeline was polished, but hopefully you get the idea.
4n1m4t1Øn
Little tool between rigging and animation departments to help automate the loading of the synoptics of the main characters.
Video player with a custom interface allowing the different departments to visualize the playblasts of the same sequence. Helps detect «raccord» issues in a sequence.
Playblast generator tool. Performs different actions related to playblast generation, naming convetion, folder structure delivery and tracking of old history playblasts.
«Papitomatic». – Tool that acts as a plugin that pushes further the Animation Studio Library by allowing to export animation data without opening Maya ! It analyzes the Maya ASCII files in search of animation data (keyframe information) and injects it into the Studio Library allowing the animator to reuse and copy animation in a totally fast and new way.
p1p3l1n3 /// l4yØvt
Pipeline mover and copier. Allows to select which scenes and characters the artist wants to work on and proceeds to «download» the content to their local machines handling all path related issues, and save the work back on the server. It also allows to modify which references will be loaded before opening Maya in order to save loading time!
Cameratronic. – Layout/Editorial Tool that allows to create the master shots of an entire sequence and movie and edit the cameras. A Camera Sequencer helper.
r1gg1ng /// crØwd5
Motion tail Autorig. Sets up controllers around a curve that handles the motion of some characters where their anatomy makes this suitable.
A dynamics parameters autoconfigurator allowing to ease the tweaking and adjustment of the different values to achieve the desired physically-based motion.
Another tool for the Crowds/Dynamics Department. Allows to automate the construction of a motion curve and their controls to handle the movement of particles
3d /// CG
July 2006, my final grade project. C /// OpenGL /// Glut /// OpenAL. Based on Craig Reynolds Steering behaviour paper, but this time, we decided to make the motion physically based as the result of forces that affect acceleration instead of velocity. Several behaviours were implemented such as wandering, path following, obstacle avoidance, eating, death and birth of particles, chasing, fleeing and finally, flocking. All these behaviours were implemented in an ecosystem of fish particles (tuna, anchovy, sharks). In order to give some sense and logic, a simple multitask decision system was implemented that was affected by two parameters: libido and hunger measured as percentages that would drop down by the passing of time and chasing/fleeing behaviors.
Procedural texture and mesh terrain generator. One of the things that i had to leave behing during my FGP was the programming of Perlin noise. Since i started tinkering with Python and Qt i decided to start a mini tool showcasing the implementation. I also used Vertex Buffer Objects to perform better on the graphics card.
First approach to computer graphics back in 2005. Done in cortona VRML 3D. Done as part of an introductory course to Computer Graphics during my third year at university.
Design /// Modeling entirely in VRML. Texturing is handpainted sometimes and others i leaned on opensource images
Coursera MOOC as an introduction to interactive programming in Python. My first approach to this programming language. The course was using an online platform to run everything. I decided to port it to PyGame so i could run it as a standalone application in my computer.
CØmpvt3r 5c13nc3
Exercises done as part of the Algorithms & DataStructures course at Princeton University. I decided to enroll in this course to improve and get a first grasp of programming complexity and performance. If i recall correctly, there were 5 weekly exercises. Normally it would take me from friday (day of the exercise release) to the next thursday dedicating 3-5 hours per day. To me it was very demanding but back in the day i was a little bit more relieved from work. Part 2 of the course explains graphs, and for the time being, it will remain undone ;P.