Human-Computer Interaction

Chang Xiao, Cheng Zhang, and Changxi Zheng
FontCode: Embedding Information in Text Documents using Glyph Perturbation.
ACM Transactions on Graphics, 2018 (Presented at SIGGRAPH 2018)

Paper (PDF) Project Page Abstract Video Bibtex
We introduce FontCode, an information embedding technique for text documents. Provided a text document with specific fonts, our method embeds user-specified information in the text by perturbing the glyphs of text characters while preserving the text content. We devise an algorithm to choose unobtrusive yet machine-recognizable glyph perturbations, leveraging a recently developed generative model that alters the glyphs of each character continuously on a font manifold. We then introduce an algorithm that embeds a user-provided message in the text document and produces an encoded document whose appearance is minimally perturbed from the original document. We also present a glyph recognition method that recovers the embedded information from an encoded document stored as a vector graphic or pixel image, or even on a printed paper. In addition, we introduce a new error-correction coding scheme that rectifies a certain number of recognition errors. Lastly, we demonstrate that our technique enables a wide array of applications, using it as a text document metadata holder, an unobtrusive optical barcode, a cryptographic message embedding scheme, and a text document signature.
 author = {Xiao, Chang and Zhang, Cheng and Zheng, Changxi},
 title = {FontCode: Embedding Information in Text Documents Using Glyph Perturbation},
 journal = {ACM Trans. Graph.},
 issue_date = {May 2018},
 volume = {37},
 number = {2},
 month = feb,
 year = {2018},
 pages = {15:1--15:16},
 articleno = {15},
 numpages = {16},
 doi = {10.1145/3152823},
Dingzeyu Li, Avinash S. Nair, Shree K. Nayar, and Changxi Zheng
AirCode: Unobtrusive Physical Tags for Digital Fabrication.
ACM User Interface Software and Technology (UIST), Oct. 2017
(Best Paper Award)

Paper (PDF) Project Page Abstract Video Bibtex
We present AirCode, a technique that allows the user to tag physically fabricated objects with given information. An AirCode tag consists of a group of carefully designed air pockets placed beneath the object surface. These air pockets are easily produced during the fabrication process of the object, without any additional material or postprocessing. Meanwhile, the air pockets affect only the scattering light transport under the surface, and thus are hard to notice to our naked eyes. But, by using a computational imaging method, the tags become detectable. We present a tool that automates the design of air pockets for the user to encode information. AirCode system also allows the user to retrieve the information from captured images via a robust decoding algorithm. We demonstrate our tagging technique with applications for metadata embedding, robotic grasping, as well as conveying object affordances.
 author = {Li, Dingzeyu and Nair, Avinash S. and Nayar, Shree K. and Zheng, Changxi},
 title = {AirCode: Unobtrusive Physical Tags for Digital Fabrication},
 booktitle = {Proceedings of the 30th Annual ACM Symposium on User Interface Software 
              and Technology},
 series = {UIST '17},
 year = {2017},
 pages = {449--460},
 publisher = {ACM},
 address = {New York, NY, USA},
Dingzeyu Li, David I.W. Levin, Wojciech Matusik, and Changxi Zheng
Acoustic Voxels: Computational Optimization of Modular Acoustic Filters.
ACM Transactions on Graphics (SIGGRAPH 2016), 35(4)

Paper (PDF) Project Page Abstract Video Bibtex
Acoustic filters have a wide range of applications, yet customizing them with desired properties is difficult. Motivated by recent progress in additive manufacturing that allows for fast prototyping of complex shapes, we present a computational approach that automates the design of acoustic filters with complex geometries. In our approach, we construct an acoustic filter comprised of a set of parameterized shape primitives, whose transmission matrices can be precomputed. Using an efficient method of simulating the transmission matrix of an assembly built from these underlying primitives, our method is able to optimize both the arrangement and the parameters of the acoustic shape primitives in order to satisfy target acoustic properties of the filter. We validate our results against industrial laboratory measurements and high-quality off-line simulations. We demonstrate that our method enables a wide range of applications including muffler design, musical wind instrument prototyping, and encoding imperceptible acoustic information into everyday objects.
  title={Acoustic Voxels: Computational Optimization of Modular Acoustic Filters},
  author={Li, Dingzeyu and Levin, David I.W. and Matusik, Wojciech and Zheng, Changxi},
  journal = {ACM Transactions on Graphics (SIGGRAPH 2016)},
  url = {}