ShotVis: Smartphone-Based visualization of OCR information from images

Biao Zhu, Hongxin Zhang, Wei Chen, Feng Xia, Ross Maciejewski

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


While visualization has been widely used as a data presentation tool in both desktop and mobile devices, the rapid visualization of information from images is still underexplored. In this work, we present a smartphone image acquisition and visualization approach for text-based data. Our prototype, ShotVis, takes images of text captured from mobile devices and extracts information for visualization. First, scattered characters in the text are processed and interactively reformulated to be stored as structured data (i.e., tables of numbers, lists of words, sentences). From there, ShotVis allows users to interactively bind visual forms to the underlying data and produce visualizations of the selected forms through touch-based interactions. In this manner, ShotVis can quickly summarize text from images into word clouds, scatterplots, and various other visualizations all through a simple click of the camera. In this way, ShotVis facilitates the interactive exploration of text data captured via cameras in smartphone devices. To demonstrate our prototype, several case studies are presented along with one user study to demonstrate the effectiveness of our approach.

Original languageEnglish (US)
Article number12
JournalACM Transactions on Multimedia Computing, Communications and Applications
StatePublished - Oct 2015


  • Cyber-physical interaction
  • Data visualization
  • Interaction
  • Smartphone
  • Touch-based interface
  • Wearable computing

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Networks and Communications


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