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Detecting path intersections in panoramic video
Given panoramic video taken along a self-intersecting path, we present a method for detecting the intersection points. This allows "virtual tours" to be synthesized by splicing the panoramic video at the intersection points. Spatial intersections are detected by finding the best-matching p...
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container_end_page | 532 vol.2 |
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container_volume | 2 |
creator | Xinding Sun Kimber, D. Foote, J. Manjunath, B.S. |
description | Given panoramic video taken along a self-intersecting path, we present a method for detecting the intersection points. This allows "virtual tours" to be synthesized by splicing the panoramic video at the intersection points. Spatial intersections are detected by finding the best-matching panoramic images from a number of nearby candidates. Each panoramic image is segmented into horizontal strips. Each strip is averaged in the vertical direction. The Fourier coefficients of the resulting 1-D data capture the rotation-invariant horizontal texture of each panoramic image. The distance between two panoramic images is calculated as the sum of the distances between their strip texture pairs at the same row positions. The intersection is chosen as the two candidate panoramic images that have the minimum distance. |
doi_str_mv | 10.1109/ICME.2002.1035667 |
format | conference_proceeding |
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This allows "virtual tours" to be synthesized by splicing the panoramic video at the intersection points. Spatial intersections are detected by finding the best-matching panoramic images from a number of nearby candidates. Each panoramic image is segmented into horizontal strips. Each strip is averaged in the vertical direction. The Fourier coefficients of the resulting 1-D data capture the rotation-invariant horizontal texture of each panoramic image. The distance between two panoramic images is calculated as the sum of the distances between their strip texture pairs at the same row positions. The intersection is chosen as the two candidate panoramic images that have the minimum distance.</description><identifier>ISBN: 9780780373044</identifier><identifier>ISBN: 0780373049</identifier><identifier>DOI: 10.1109/ICME.2002.1035667</identifier><language>eng</language><publisher>IEEE</publisher><subject>Cities and towns ; Global Positioning System ; Image matching ; Image segmentation ; Inspection ; Laboratories ; Satellite navigation systems ; Splicing ; Strips ; Sun</subject><ispartof>Proceedings. 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IEEE International Conference on Multimedia and Expo</title><addtitle>ICME</addtitle><description>Given panoramic video taken along a self-intersecting path, we present a method for detecting the intersection points. This allows "virtual tours" to be synthesized by splicing the panoramic video at the intersection points. Spatial intersections are detected by finding the best-matching panoramic images from a number of nearby candidates. Each panoramic image is segmented into horizontal strips. Each strip is averaged in the vertical direction. The Fourier coefficients of the resulting 1-D data capture the rotation-invariant horizontal texture of each panoramic image. The distance between two panoramic images is calculated as the sum of the distances between their strip texture pairs at the same row positions. The intersection is chosen as the two candidate panoramic images that have the minimum distance.</description><subject>Cities and towns</subject><subject>Global Positioning System</subject><subject>Image matching</subject><subject>Image segmentation</subject><subject>Inspection</subject><subject>Laboratories</subject><subject>Satellite navigation systems</subject><subject>Splicing</subject><subject>Strips</subject><subject>Sun</subject><isbn>9780780373044</isbn><isbn>0780373049</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2002</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotj89KAzEYxAMiKHUfQLzsC-z2y__kKGvVQosXPZcv2UQjdrdsguDbG7HDwPCbw8AQckuhpxTsejvsNz0DYD0FLpXSF6Sx2kA11xyEuCJNzp9Qxa2UBq7J-iGU4Eua3tsTlo82TSUs-a-Zp1ypttO84DH59juNYb4hlxG_cmjOuSJvj5vX4bnbvTxth_tdlxg1pbPOKuMVUDSOQozomRSj9lRjiE5EFEwbwYPmlDonAQ2XMCo0DJCNlVbk7n83hRAOpyUdcfk5nG_xXzTmQj4</recordid><startdate>2002</startdate><enddate>2002</enddate><creator>Xinding Sun</creator><creator>Kimber, D.</creator><creator>Foote, J.</creator><creator>Manjunath, B.S.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2002</creationdate><title>Detecting path intersections in panoramic video</title><author>Xinding Sun ; Kimber, D. ; Foote, J. ; Manjunath, B.S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i218t-9b968c601a8b10ffac254d7c17aefb4fa427843e7311bb50a8350d6a820a2da83</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2002</creationdate><topic>Cities and towns</topic><topic>Global Positioning System</topic><topic>Image matching</topic><topic>Image segmentation</topic><topic>Inspection</topic><topic>Laboratories</topic><topic>Satellite navigation systems</topic><topic>Splicing</topic><topic>Strips</topic><topic>Sun</topic><toplevel>online_resources</toplevel><creatorcontrib>Xinding Sun</creatorcontrib><creatorcontrib>Kimber, D.</creatorcontrib><creatorcontrib>Foote, J.</creatorcontrib><creatorcontrib>Manjunath, B.S.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEL</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Xinding Sun</au><au>Kimber, D.</au><au>Foote, J.</au><au>Manjunath, B.S.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Detecting path intersections in panoramic video</atitle><btitle>Proceedings. IEEE International Conference on Multimedia and Expo</btitle><stitle>ICME</stitle><date>2002</date><risdate>2002</risdate><volume>2</volume><spage>529</spage><epage>532 vol.2</epage><pages>529-532 vol.2</pages><isbn>9780780373044</isbn><isbn>0780373049</isbn><abstract>Given panoramic video taken along a self-intersecting path, we present a method for detecting the intersection points. This allows "virtual tours" to be synthesized by splicing the panoramic video at the intersection points. Spatial intersections are detected by finding the best-matching panoramic images from a number of nearby candidates. Each panoramic image is segmented into horizontal strips. Each strip is averaged in the vertical direction. The Fourier coefficients of the resulting 1-D data capture the rotation-invariant horizontal texture of each panoramic image. The distance between two panoramic images is calculated as the sum of the distances between their strip texture pairs at the same row positions. The intersection is chosen as the two candidate panoramic images that have the minimum distance.</abstract><pub>IEEE</pub><doi>10.1109/ICME.2002.1035667</doi><oa>free_for_read</oa></addata></record> |
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ispartof | Proceedings. IEEE International Conference on Multimedia and Expo, 2002, Vol.2, p.529-532 vol.2 |
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language | eng |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Cities and towns Global Positioning System Image matching Image segmentation Inspection Laboratories Satellite navigation systems Splicing Strips Sun |
title | Detecting path intersections in panoramic video |
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