Abstract
Knowledge workers need effective annotation tools to assimilate information. Unfortunately many digital annotators are limited in the range of document that they accept. Those that do accept many different documents do so by converting documents to images, thus losing any awareness about the original content of the document. We introduce a digital note taker that is both universal and content aware. By constructing a hierarchical context tree of document images, the structure of a document is inferred from the image. This hierarchical context tree is shown to be useful by demonstrating how it facilitates selection of document elements, reflowing documents to accommodate inserted notes, and expanding the context of links. PixelJot, and implementation of these ideas, demonstrates their feasibility.
Degree
MS
College and Department
Physical and Mathematical Sciences; Computer Science
Rights
http://lib.byu.edu/about/copyright/
BYU ScholarsArchive Citation
Harris, Mitchell Kent, "Pixel Based Note Taking through Perceptual Structure Inference" (2010). Theses and Dissertations. 2282.
https://scholarsarchive.byu.edu/etd/2282
Date Submitted
2010-10-08
Document Type
Thesis
Handle
http://hdl.lib.byu.edu/1877/etd3987
Keywords
annotation, perception, HCI
Language
English