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

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