  While paper instructions are one of the mainstream medium for sharing
knowledge, consuming such instructions and translating them into activities are
inefficient due to the lack of connectivity with physical environment. We
present PaperToPlace, a novel workflow comprising an authoring pipeline, which
allows the authors to rapidly transform and spatialize existing paper
instructions into MR experience, and a consumption pipeline, which
computationally place each instruction step at an optimal location that is easy
to read and do not occlude key interaction areas. Our evaluations of the
authoring pipeline with 12 participants demonstrated the usability of our
workflow and the effectiveness of using a machine learning based approach to
help extracting the spatial locations associated with each steps. A second
within-subject study with another 12 participants demonstrates the merits of
our consumption pipeline by reducing efforts of context switching, delivering
the segmented instruction steps and offering the hands-free affordances.
