<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "https://jats.nlm.nih.gov/nlm-dtd/publishing/3.0/journalpublishing3.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="3.0" xml:lang="en">
<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Annals</journal-id>
<journal-title-group>
<journal-title>ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Annals</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9050</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/isprs-annals-IV-2-W4-407-2017</article-id>
<title-group>
<article-title>A MAPPING METHOD OF SLAM BASED ON LOOK UP TABLE</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Wang</surname>
<given-names>Z.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Li</surname>
<given-names>J.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Wang</surname>
<given-names>A.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Wang</surname>
<given-names>J.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>School of Navigation and Aerospace Engineering, Information Engineering University, Zhengzhou 450000, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>14</day>
<month>09</month>
<year>2017</year>
</pub-date>
<volume>IV-2/W4</volume>
<fpage>407</fpage>
<lpage>410</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2017 Z. Wang et al.</copyright-statement>
<copyright-year>2017</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://isprs-annals.copernicus.org/articles/IV-2-W4/407/2017/isprs-annals-IV-2-W4-407-2017.html">This article is available from https://isprs-annals.copernicus.org/articles/IV-2-W4/407/2017/isprs-annals-IV-2-W4-407-2017.html</self-uri>
<self-uri xlink:href="https://isprs-annals.copernicus.org/articles/IV-2-W4/407/2017/isprs-annals-IV-2-W4-407-2017.pdf">The full text article is available as a PDF file from https://isprs-annals.copernicus.org/articles/IV-2-W4/407/2017/isprs-annals-IV-2-W4-407-2017.pdf</self-uri>
<abstract>
<p>In the last years several V-SLAM(Visual Simultaneous Localization and Mapping) approaches have appeared showing impressive
reconstructions of the world. However these maps are built with far more than the required information. This limitation comes from the
whole process of each key-frame. In this paper we present for the first time a mapping method based on the LOOK UP TABLE(LUT)
for visual SLAM that can improve the mapping effectively. As this method relies on extracting features in each cell divided from image,
it can get the pose of camera that is more representative of the whole key-frame. The tracking direction of key-frames is obtained by
counting the number of parallax directions of feature points. LUT stored all mapping needs the number of cell corresponding to the
tracking direction which can reduce the redundant information in the key-frame, and is more efficient to mapping. The result shows
that a better map with less noise is build using less than one-third of the time. We believe that the capacity of LUT efficiently building
maps makes it a good choice for the community to investigate in the scene reconstruction problems.</p>
</abstract>
<counts><page-count count="4"/></counts>
</article-meta>
</front>
<body/>
<back>
</back>
</article>