Automatic Determination of Text Readability over Textured Backgrounds for Augmented Reality Systems
This paper describes a pattern recognition approach to determine readability of text labels in augmented reality systems. In many augmented reality applications, one of the ways in which information is presented to the user is to place a text label over the area of interest. However, if this informa...
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| Veröffentlicht in: | Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality S. 224 - 230 |
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| Sprache: | Englisch |
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Washington, DC, USA
IEEE Computer Society
02.11.2004
IEEE |
| Schriftenreihe: | ACM Other Conferences |
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| ISBN: | 0769521916, 9780769521916 |
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| Abstract | This paper describes a pattern recognition approach to determine readability of text labels in augmented reality systems. In many augmented reality applications, one of the ways in which information is presented to the user is to place a text label over the area of interest. However, if this information is placed over very busy and textured backgrounds, this can affect the readability of the text. The goal of this work was to identify methods of quantitatively describing conditions under which such text would be readable or unreadable. We used texture properties and other visual features to determine if a text placed on a particular background would be readable or not. Based on these features, a supervised classifier was built that was trained using data collected from human subjects' judgment of text readability. Using a rather small training set of about 400 human evaluations over 50 heterogeneous textures the system is able to achieve a correct classification rate of over 85%. |
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| AbstractList | This paper describes a pattern recognition approach to determine readability of text labels in augmented reality systems. In many augmented reality applications, one of the ways in which information is presented to the user is to place a text label over the area of interest. However, if this information is placed over very busy and textured backgrounds, this can affect the readability of the text. The goal of this work was to identify methods of quantitatively describing conditions under which such text would be readable or unreadable. We used texture properties and other visual features to determine if a text placed on a particular background would be readable or not. Based on these features, a supervised classifier was built that was trained using data collected from human subjects' judgment of text readability. Using a rather small training set of about 400 human evaluations over 50 heterogeneous textures the system is able to achieve a correct classification rate of over 85%. This paper describes a pattern recognition approach to determine readability of text labels in augmented reality systems. In many augmented reality applications, one of the ways in which information is presented to the user is to place a text label over the area of interest. However, if this information is placed over very busy and textured backgrounds, this can affect the readability of the text. The goal of this work was to identify methods of quantitatively describing conditions under which such text would be readable or unreadable. We used texture properties and other visual features to determine if a text placed on a particular background would be readable or not. Based on these features, a supervised classifier was built that was trained using data collected front human subjects' judgment of text readability. Using a rather small training set of about 400 human evaluations over 50 heterogeneous textures the system is able to achieve a correct classification rate of over 85%. |
| Author | Tuceryan, Mihran Leykin, Alex |
| Author_xml | – sequence: 1 givenname: Alex surname: Leykin fullname: Leykin, Alex organization: Indiana University, Bloomington – sequence: 2 givenname: Mihran surname: Tuceryan fullname: Tuceryan, Mihran organization: Indiana University - Purdue University Indianapolis (IUPUI) |
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| Snippet | This paper describes a pattern recognition approach to determine readability of text labels in augmented reality systems. In many augmented reality... |
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| SubjectTerms | Application software Augmented reality Computer science Computing methodologies Computing methodologies -- Machine learning Computing methodologies -- Machine learning -- Learning paradigms Computing methodologies -- Machine learning -- Learning paradigms -- Supervised learning Computing methodologies -- Machine learning -- Learning paradigms -- Supervised learning -- Supervised learning by classification Computing methodologies -- Machine learning -- Machine learning algorithms Computing methodologies -- Machine learning -- Machine learning algorithms -- Feature selection Computing methodologies -- Machine learning -- Machine learning approaches Computing methodologies -- Machine learning -- Machine learning approaches -- Classification and regression trees Graphics Humans Information science Interference Labeling Layout Pattern recognition |
| Title | Automatic Determination of Text Readability over Textured Backgrounds for Augmented Reality Systems |
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