The Challenge
Luminar’s ability to exceed sight range goals relied on ultra-precise, expanded image annotation. With safety as the driving priority, quality and consistency were more than standard criteria, they were life or death imperatives.
Having been down this road before, Luminar had grown frustrated with outsourcing solutions that could annotate large volumes of data, but significantly missed the mark when it came to complexity and standards. The intricacy and sophistication of the work required was far more challenging than untrained resources with disparate leadership could handle. Proficiency in the most robust object detection was critical to the vision, and there was no room for error.
These challenges necessitated the mobilization of a highly trained and experienced workforce deeply committed to the outcome of every task and associated minutiae.
Complex requirements included annotating every individual element within an image, whether perceived as relevant to the driver’s view or not. From humans to animals, empty roads to unknown objects—every element had to be accounted for.
Those oddities that humans recognize and respond to but could be problematic for machines, like background clutter, distance, and partial view obstruction, were also incorporated. Plus, Luminar’s model demanded unique labeling requirements for items such as sidewalks, unreachable lanes, gas stations, parking lots, trees, and signage—attention to every detail was essential.
A final requirement for this already complex project was that Luminar required the work to be completed within its own tool. The inability for many outsourcing providers to adapt to an outside tool and for Luminar to adopt an insufficient platform was costing them time and money.
