Accessories Web Configurator - MOPAR, GM
3DS Max - Mental Ray // Maya - Arnold // Python
I worked on this project from 2009 until about 2022 in it’s various iterations. I worked my way up to lead our team of 3D artists on this project, to create high-quality imagery for a web configurator designed for the MOPAR web store, and previously for GM accessories. We visualized each vehicle model with a wide range of accessories, providing users with a comprehensive 5-angle turnaround view. This configurator enabled potential customers to see different accessory options integrated into the vehicle images, enhancing their decision-making process.
The vehicle models were mostly sourced from the OEM and we optimized the vehicles and modeled the accessories. Originally the project was Java 3D based. Though interesting and remarkable for using web 3D very early on, it didn’t provide the level of realism the clients really wanted. At that time, we felt using pre-rendered images was the best way to give the customer the most realistic representation of what they were purchasing, so I was asked to develop a process to replace the product with a pre-rendered version that was composited through JavaScript on the web.
The challenge was to create a process for efficiently rendering each configurable piece of the vehicle with an alpha channel, so numerous images could be composited on the fly, on the website. To solve that I used 3DS Max’s scene states and Mental Ray to batch render each piece, at every angle, in every paint color.
Eventually, scene states in 3DS Max proved to be too unstable, and there were still a lot of manual steps in the process. We wanted to be able to spend more time on quality modeling and less on setting up the scene and processing the images afterward. To solve that problem I made use of the Render Layers feature in Maya.
I set up templates in Maya for HDRI Lighting, and material libraries for consistency and to help automate the process, I wrote custom scripts using Python to facilitate the creation and management of namespaces, and render layers, considerably cutting down the time needed to set up the renders, and process the images afterward.
The project successfully delivered a sophisticated web configurator that was well-received by the clients, and significantly improved user engagement and satisfaction.
I grew a lot from this project. I gained a lot of experience in modeling, lighting and technical aspects of 3D, and I eventually learned a lot about planning and leadership,
and Jira.