Mathematical Colloquium : Pedestrian Location Estimation by a Single Image from Human-borne Camera

00:00 17-08-2010
&amp;lt;p style="TEXT-ALIGN: left; MARGIN: 0cm 0cm 0pt; unicode-bidi: embed; DIRECTION: ltr" class="MsoNormal"&amp;gt;&amp;lt;span style="COLOR: black; mso-fareast-font-family: &amp;amp;#39;Times New Roman&amp;amp;#39;"&amp;gt;&amp;lt;font face="Arial, Helvetica, sans-serif"&amp;gt;&amp;lt;font size="2"&amp;gt;We propose and introduce a practical pedestrian location method that exploits only a human-borne camera and runs on line. Pedestrian &amp;lt;/font&amp;gt;&amp;lt;/font&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt; &amp;lt;p style="MARGIN: 0cm 0cm 0pt" class="MsoPlainText"&amp;gt;&amp;lt;span style="COLOR: black"&amp;gt;&amp;lt;font face="Arial, Helvetica, sans-serif"&amp;gt;&amp;lt;font size="2"&amp;gt;&amp;amp;nbsp;localization is an essential technology for walking navigation,&amp;amp;nbsp;especially for visually impaired people. Unfortunately, commonly used&amp;lt;/font&amp;gt;&amp;lt;/font&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt; &amp;lt;p style="MARGIN: 0cm 0cm 0pt" class="MsoPlainText"&amp;gt;&amp;lt;span style="COLOR: black"&amp;gt;&amp;lt;font face="Arial, Helvetica, sans-serif"&amp;gt;&amp;lt;font size="2"&amp;gt;&amp;amp;nbsp;GPS is not available or unreliable in underground shopping mall, indoor&amp;amp;nbsp;paths, and urban streets with tall buildings. Our proposed method can&amp;lt;/font&amp;gt;&amp;lt;/font&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt; &amp;lt;p style="MARGIN: 0cm 0cm 0pt" class="MsoPlainText"&amp;gt;&amp;lt;span style="COLOR: black"&amp;gt;&amp;lt;font face="Arial, Helvetica, sans-serif"&amp;gt;&amp;lt;font size="2"&amp;gt;&amp;amp;nbsp;estimate current position only by one image of the first person vision&amp;amp;nbsp;camera, assuming that videos that were taken by walking through the same&amp;lt;/font&amp;gt;&amp;lt;/font&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt; &amp;lt;p style="MARGIN: 0cm 0cm 0pt" class="MsoPlainText"&amp;gt;&amp;lt;span style="COLOR: black"&amp;gt;&amp;lt;font face="Arial, Helvetica, sans-serif"&amp;gt;&amp;lt;font size="2"&amp;gt;&amp;amp;nbsp;path are given to our system in advance. As a first person camera is&amp;amp;nbsp;mounted on a body of a pedestrian, both the images taken by human-borne&amp;lt;/font&amp;gt;&amp;lt;/font&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt; &amp;lt;p style="MARGIN: 0cm 0cm 0pt" class="MsoPlainText"&amp;gt;&amp;lt;span style="COLOR: black"&amp;gt;&amp;lt;font face="Arial, Helvetica, sans-serif"&amp;gt;&amp;lt;font size="2"&amp;gt;&amp;amp;nbsp;camera and the videos given to the system always includes obstacles such&amp;amp;nbsp;as other pedestrians. The proposed method adopts local feature&amp;lt;/font&amp;gt;&amp;lt;/font&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt; &amp;lt;p style="MARGIN: 0cm 0cm 0pt" class="MsoPlainText"&amp;gt;&amp;lt;span style="COLOR: black"&amp;gt;&amp;lt;font face="Arial, Helvetica, sans-serif"&amp;gt;&amp;lt;font size="2"&amp;gt;&amp;amp;nbsp;descriptors (e.g. SIFT and SURF) and utilizes general image retrieval&amp;amp;nbsp;approach, but it exploits some conditions that are specific to first&amp;lt;/font&amp;gt;&amp;lt;/font&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt; &amp;lt;p style="MARGIN: 0cm 0cm 0pt" class="MsoPlainText"&amp;gt;&amp;lt;span style="COLOR: black"&amp;gt;&amp;lt;font face="Arial, Helvetica, sans-serif"&amp;gt;&amp;lt;font size="2"&amp;gt;&amp;amp;nbsp;person vision camera so that it can produce reliable localization&amp;amp;nbsp;results. We take up one of the typical and difficult paths for&amp;lt;/font&amp;gt;&amp;lt;/font&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt; &amp;lt;p style="MARGIN: 0cm 0cm 0pt" class="MsoPlainText"&amp;gt;&amp;lt;span style="COLOR: black"&amp;gt;&amp;lt;font face="Arial, Helvetica, sans-serif"&amp;gt;&amp;lt;font size="2"&amp;gt;&amp;amp;nbsp;experiment and evaluation; a path that starts from underground level of&amp;amp;nbsp;Tokyo station area to the ground level where tall buildings cover the&amp;lt;/font&amp;gt;&amp;lt;/font&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt; &amp;lt;p style="MARGIN: 0cm 0cm 0pt" class="MsoPlainText"&amp;gt;&amp;lt;span style="COLOR: black"&amp;gt;&amp;lt;font face="Arial, Helvetica, sans-serif"&amp;gt;&amp;lt;font size="2"&amp;gt;&amp;amp;nbsp;sky. The result shows the proposed method can work well even in urban&amp;amp;nbsp;areas like there.&amp;lt;/font&amp;gt;&amp;lt;/font&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt; &amp;lt;p style="MARGIN: 0cm 0cm 0pt" class="MsoPlainText"&amp;gt;&amp;lt;span style="COLOR: black"&amp;gt;&amp;lt;font face="Arial, Helvetica, sans-serif"&amp;gt;&amp;lt;font size="2"&amp;gt;&amp;amp;nbsp;We also present our recent works on Massive Sensing (Sensor fusion with&amp;amp;nbsp;support of massive computing environment) and Mixed Reality (a.k.a.&amp;lt;/font&amp;gt;&amp;lt;/font&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt; &amp;lt;p style="MARGIN: 0cm 0cm 0pt" class="MsoPlainText"&amp;gt;&amp;lt;span style="COLOR: black"&amp;gt;&amp;lt;font face="Arial, Helvetica, sans-serif"&amp;gt;&amp;lt;font size="2"&amp;gt;&amp;amp;nbsp;Augmented Reality), including free viewpoint video generation, visually&amp;amp;nbsp;support of vehicle driver, see-through vision for pedestrian, and so on.&amp;lt;/font&amp;gt;&amp;lt;/font&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;&amp;lt;SPAN STYLE="display: none"&amp;gt; &amp;lt;P&amp;gt;Acetylenide minutes, pointedly? 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