  The convergence of the physical and digital realms has ushered in a new era
of immersive experiences and seamless interactions. As the boundaries between
the real world and virtual environments blur and result in a "mixed reality,"
there arises a need for robust and efficient methods to connect physical
objects with their virtual counterparts. In this thesis, we present a novel
approach to bridging this gap through the design, fabrication, and detection of
embedded machine-readable markers.
  We categorize the proposed marking approaches into three distinct categories:
natural markers, structural markers, and internal markers. Natural markers,
such as those used in SensiCut, are inherent fingerprints of objects repurposed
as machine-readable identifiers, while structural markers, such as StructCode
and G-ID, leverage the structural artifacts in objects that emerge during the
fabrication process itself. Internal markers, such as InfraredTag and
BrightMarker, are embedded inside fabricated objects using specialized
materials. Leveraging a combination of methods from computer vision, machine
learning, computational imaging, and material science, the presented approaches
offer robust and versatile solutions for object identification, tracking, and
interaction.
  These markers, seamlessly integrated into real-world objects, effectively
communicate an object's identity, origin, function, and interaction,
functioning as gateways to "ubiquitous metadata" - a concept where metadata is
embedded into physical objects, similar to metadata in digital files. Across
the different chapters, we demonstrate the applications of the presented
methods in diverse domains, including product design, manufacturing, retail,
logistics, education, entertainment, security, and sustainability.
