🤖 AI Summary
This work addresses the aesthetic and tactile compromises inherent in existing fabric-based interaction techniques, which often rely on visible markers or added electronic modules. The authors propose a method that directly integrates near-infrared (NIR)-absorbing yarns into textiles to create visually imperceptible yet NIR-camera-readable markers. They introduce a co-designed weaving toolkit, five visual camouflage strategies, and a camera-based detection and decoding pipeline, enabling seamless integration of such invisible markers into handwoven, jacquard, and industrially produced fabrics for the first time. The approach supports encoding schemes including QR codes and ArUco markers, as well as deformation tracking, effectively balancing aesthetics, haptic quality, and functionality while offering scalability from bespoke to mass production.
📝 Abstract
Textiles are increasingly explored as media for interacting with digital information. However, many of the existing approaches rely on visible tags, printed overlays, or electronic modules that compromise the fabric's aesthetic and tactile qualities. To address this, we present InvisIto, a method for weaving visually unobtrusive yet machine-readable infrared markers directly into fabrics using near-infrared (NIR)-absorbing yarns. Although these yarns look similar to standard fibers in ambient light, they produce strong contrast in NIR imaging. Our method includes: (1) a design tool that helps users easily embed infrared markers into weaving drafts, (2) five disguising strategies that further reduce marker visibility under ambient light, and (3) a camera-based detection pipeline for decoding and tracking the woven markers. InvisIto supports both woven QR codes for data encoding and woven ArUco markers for binary input and deformation tracking. We demonstrate applications across hand weaving, Jacquard weaving, and industrial fabrication, showing that InvisIto supports scalable interaction and fabrication from bespoke artifacts to mass production.