Starting from a sketch and real material photography, I built a CMF system for an outdoor product family, first applied to a backpack, then extended to a tent using the same material logic and workflow. The materials weren't pulled from a library. Cotton, waterproof technical fabric, and velcro were photographed from physical samples and fed directly into Vizcom as references.

Instead of pulling materials from stock libraries, I photographed physical fabric samples with my phone: double-layer cotton, waterproof technical fabric, velcro. Those images went directly into Vizcom as material references. The sketch provided the form; the photos provided the surface language. Once the system was defined on the backpack, I built a moodboard with the same material logic and applied it to a tent concept.

The most deliberate CMF decision was placing double-layer cotton texture on the lower section of the bag, the zone that takes the most abrasion in real use. The material choice made functional sense before it made aesthetic sense. When the same logic was applied to the tent, the olive, mustard, and technical fabric palette transferred without friction. Two products, one coherent system.

A material-grounded CMF system documented across two product categories, with a full exploration canvas showing how real material references behave inside an AI rendering workflow.

Real material photography produces results that stock textures don't. The imperfections and weave irregularities in a phone photo give the render a physical credibility that clean library textures lose. It takes five minutes to photograph a fabric sample. It's worth it. And once a CMF system is defined on one product, extending it to a second is faster than starting from scratch, the material language does the work.