rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Sketch recognition on mobile devices
  name:
    name part: Lucchese, George
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Hammond, Tracy
    role:
      role term: thesis advisor.
  name:
    name part: Texas A & M University
    role:
      role term: degree granting institution.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: txu
    date issued: 2013
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (vii, 47 pages) : color illustrations.
  abstract: Sketch recognition allows computers to understand and model hand drawn sketches and diagrams. Traditionally sketch recognition systems required a pen based PC interface, but powerful mobile devices such as tablets and smartphones can provide a new platform for sketch recognition systems. We describe a new sketch recognition library, Strontium (SrL) that combines several existing sketch recognition libraries modified to run on both personal computers and on the Android platform. We analyzed the recognition speed and accuracy implications of performing low-level shape recognition on smartphones with touch screens. We found that there is a large gap in recognition speed on mobile devices between recognizing simple shapes and more complex ones, suggesting that mobile sketch interface designers limit the complexity of their sketch domains. We also found that a low sampling rate on mobile devices can affect recognition accuracy of complex and curved shapes. Despite this, we found no evidence to suggest that using a finger as an input implement leads to a decrease in simple shape recognition accuracy. These results show that the same geometric shape recognizers developed for pen applications can be used in mobile applications, provided that developers keep shape domains simple and ensure that input sampling rate is kept as high as possible. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/148264
  note: by George Robert Lucchese.
  note: "Major Subject: Computer Science"
  note: Includes vita.
  note: Master of Science Texas A & M University 2012 http://hdl.handle.net/1969.1/148264
  note: Includes bibliographical references.
  note: Text (Thesis)
  subject:
    topic: Major Computer Science
  subject:
    topic: Distributed Recognition
  subject:
    topic: Mobile Devices
  subject:
    topic: Touch Input
  subject:
    topic: Sketch Recognition
  identifier: http://hdl.handle.net/1969.1/148264
  record info:
    record content source: TXA
    record creation date: 131212
    record change date: 20151206090615.0
    record identifier: in00003420556
    language of cataloging:
      language term: eng