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Rachida Amjoun, and Wolfgang Strasser, Predictive-DCT Coding for 3D Mesh Sequences Compression. JVRB - Journal of Virtual Reality and Broadcasting, 5(2008), no. 6. (urn:nbn:de:0009-6-14446)
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%0 Journal Article %T Predictive-DCT Coding for 3D Mesh Sequences Compression %A Amjoun, Rachida %A Strasser, Wolfgang %J JVRB - Journal of Virtual Reality and Broadcasting %D 2008 %V 5(2008) %N 6 %@ 1860-2037 %F amjoun2008 %X This paper proposes a new compression algorithm fordynamic 3d meshes. In such a sequence of meshes,neighboring vertices have a strong tendency to behavesimilarly and the degree of dependencies between theirlocations in two successive frames is very large which canbe efficiently exploited using a combination of Predictiveand DCT coders (PDCT). Our strategy gathers meshvertices of similar motions into clusters, establish alocal coordinate frame (LCF) for each cluster andencodes frame by frame and each cluster separately. Thevertices of each cluster have small variation over atime relative to the LCF. Therefore, the location ofeach new vertex is well predicted from its location inthe previous frame relative to the LCF of its cluster.The difference between the original and the predictedlocal coordinates are then transformed into frequencydomain using DCT. The resulting DCT coefficients arequantized and compressed with entropy coding. Theoriginal sequence of meshes can be reconstructed from only a few non-zero DCT coefficients without significant loss in visual quality. Experimental results show that our strategy outperforms or comes close to other coders. %L 004 %K Animation %K DCT %K animated mesh compression %K clustering %K local coordinate frame %K predictive coding %R 10.20385/1860-2037/5.2008.6 %U http://nbn-resolving.de/urn:nbn:de:0009-6-14446 %U http://dx.doi.org/10.20385/1860-2037/5.2008.6Download
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@Article{amjoun2008, author = "Amjoun, Rachida and Strasser, Wolfgang", title = "Predictive-DCT Coding for 3D Mesh Sequences Compression", journal = "JVRB - Journal of Virtual Reality and Broadcasting", year = "2008", volume = "5(2008)", number = "6", keywords = "Animation; DCT; animated mesh compression; clustering; local coordinate frame; predictive coding", abstract = "This paper proposes a new compression algorithm fordynamic 3d meshes. In such a sequence of meshes,neighboring vertices have a strong tendency to behavesimilarly and the degree of dependencies between theirlocations in two successive frames is very large which canbe efficiently exploited using a combination of Predictiveand DCT coders (PDCT). Our strategy gathers meshvertices of similar motions into clusters, establish alocal coordinate frame (LCF) for each cluster andencodes frame by frame and each cluster separately. Thevertices of each cluster have small variation over atime relative to the LCF. Therefore, the location ofeach new vertex is well predicted from its location inthe previous frame relative to the LCF of its cluster.The difference between the original and the predictedlocal coordinates are then transformed into frequencydomain using DCT. The resulting DCT coefficients arequantized and compressed with entropy coding. Theoriginal sequence of meshes can be reconstructed from only a few non-zero DCT coefficients without significant loss in visual quality. Experimental results show that our strategy outperforms or comes close to other coders.", issn = "1860-2037", doi = "10.20385/1860-2037/5.2008.6", url = "http://nbn-resolving.de/urn:nbn:de:0009-6-14446" }Download
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TY - JOUR AU - Amjoun, Rachida AU - Strasser, Wolfgang PY - 2008 DA - 2008// TI - Predictive-DCT Coding for 3D Mesh Sequences Compression JO - JVRB - Journal of Virtual Reality and Broadcasting VL - 5(2008) IS - 6 KW - Animation KW - DCT KW - animated mesh compression KW - clustering KW - local coordinate frame KW - predictive coding AB - This paper proposes a new compression algorithm fordynamic 3d meshes. In such a sequence of meshes,neighboring vertices have a strong tendency to behavesimilarly and the degree of dependencies between theirlocations in two successive frames is very large which canbe efficiently exploited using a combination of Predictiveand DCT coders (PDCT). Our strategy gathers meshvertices of similar motions into clusters, establish alocal coordinate frame (LCF) for each cluster andencodes frame by frame and each cluster separately. Thevertices of each cluster have small variation over atime relative to the LCF. Therefore, the location ofeach new vertex is well predicted from its location inthe previous frame relative to the LCF of its cluster.The difference between the original and the predictedlocal coordinates are then transformed into frequencydomain using DCT. The resulting DCT coefficients arequantized and compressed with entropy coding. Theoriginal sequence of meshes can be reconstructed from only a few non-zero DCT coefficients without significant loss in visual quality. Experimental results show that our strategy outperforms or comes close to other coders. SN - 1860-2037 UR - http://nbn-resolving.de/urn:nbn:de:0009-6-14446 DO - 10.20385/1860-2037/5.2008.6 ID - amjoun2008 ER -Download
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<?xml version="1.0" encoding="UTF-8"?> <b:Sources SelectedStyle="" xmlns:b="http://schemas.openxmlformats.org/officeDocument/2006/bibliography" xmlns="http://schemas.openxmlformats.org/officeDocument/2006/bibliography" > <b:Source> <b:Tag>amjoun2008</b:Tag> <b:SourceType>ArticleInAPeriodical</b:SourceType> <b:Year>2008</b:Year> <b:PeriodicalTitle>JVRB - Journal of Virtual Reality and Broadcasting</b:PeriodicalTitle> <b:Volume>5(2008)</b:Volume> <b:Issue>6</b:Issue> <b:Url>http://nbn-resolving.de/urn:nbn:de:0009-6-14446</b:Url> <b:Url>http://dx.doi.org/10.20385/1860-2037/5.2008.6</b:Url> <b:Author> <b:Author><b:NameList> <b:Person><b:Last>Amjoun</b:Last><b:First>Rachida</b:First></b:Person> <b:Person><b:Last>Strasser</b:Last><b:First>Wolfgang</b:First></b:Person> </b:NameList></b:Author> </b:Author> <b:Title>Predictive-DCT Coding for 3D Mesh Sequences Compression</b:Title> <b:Comments>This paper proposes a new compression algorithm fordynamic 3d meshes. In such a sequence of meshes,neighboring vertices have a strong tendency to behavesimilarly and the degree of dependencies between theirlocations in two successive frames is very large which canbe efficiently exploited using a combination of Predictiveand DCT coders (PDCT). Our strategy gathers meshvertices of similar motions into clusters, establish alocal coordinate frame (LCF) for each cluster andencodes frame by frame and each cluster separately. Thevertices of each cluster have small variation over atime relative to the LCF. Therefore, the location ofeach new vertex is well predicted from its location inthe previous frame relative to the LCF of its cluster.The difference between the original and the predictedlocal coordinates are then transformed into frequencydomain using DCT. The resulting DCT coefficients arequantized and compressed with entropy coding. Theoriginal sequence of meshes can be reconstructed from only a few non-zero DCT coefficients without significant loss in visual quality. Experimental results show that our strategy outperforms or comes close to other coders.</b:Comments> </b:Source> </b:Sources>Download
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PT Journal AU Amjoun, R Strasser, W TI Predictive-DCT Coding for 3D Mesh Sequences Compression SO JVRB - Journal of Virtual Reality and Broadcasting PY 2008 VL 5(2008) IS 6 DI 10.20385/1860-2037/5.2008.6 DE Animation; DCT; animated mesh compression; clustering; local coordinate frame; predictive coding AB This paper proposes a new compression algorithm fordynamic 3d meshes. In such a sequence of meshes,neighboring vertices have a strong tendency to behavesimilarly and the degree of dependencies between theirlocations in two successive frames is very large which canbe efficiently exploited using a combination of Predictiveand DCT coders (PDCT). Our strategy gathers meshvertices of similar motions into clusters, establish alocal coordinate frame (LCF) for each cluster andencodes frame by frame and each cluster separately. Thevertices of each cluster have small variation over atime relative to the LCF. Therefore, the location ofeach new vertex is well predicted from its location inthe previous frame relative to the LCF of its cluster.The difference between the original and the predictedlocal coordinates are then transformed into frequencydomain using DCT. The resulting DCT coefficients arequantized and compressed with entropy coding. Theoriginal sequence of meshes can be reconstructed from only a few non-zero DCT coefficients without significant loss in visual quality. Experimental results show that our strategy outperforms or comes close to other coders. ERDownload
Mods
<mods> <titleInfo> <title>Predictive-DCT Coding for 3D Mesh Sequences Compression</title> </titleInfo> <name type="personal"> <namePart type="family">Amjoun</namePart> <namePart type="given">Rachida</namePart> </name> <name type="personal"> <namePart type="family">Strasser</namePart> <namePart type="given">Wolfgang</namePart> </name> <abstract>This paper proposes a new compression algorithm for dynamic 3d meshes. In such a sequence of meshes, neighboring vertices have a strong tendency to behave similarly and the degree of dependencies between their locations in two successive frames is very large which can be efficiently exploited using a combination of Predictive and DCT coders (PDCT). Our strategy gathers mesh vertices of similar motions into clusters, establish a local coordinate frame (LCF) for each cluster and encodes frame by frame and each cluster separately. The vertices of each cluster have small variation over a time relative to the LCF. Therefore, the location of each new vertex is well predicted from its location in the previous frame relative to the LCF of its cluster. The difference between the original and the predicted local coordinates are then transformed into frequency domain using DCT. The resulting DCT coefficients are quantized and compressed with entropy coding. The original sequence of meshes can be reconstructed from only a few non-zero DCT coefficients without significant loss in visual quality. Experimental results show that our strategy outperforms or comes close to other coders.</abstract> <subject> <topic>Animation</topic> <topic>DCT</topic> <topic>animated mesh compression</topic> <topic>clustering</topic> <topic>local coordinate frame</topic> <topic>predictive coding</topic> </subject> <classification authority="ddc">004</classification> <relatedItem type="host"> <genre authority="marcgt">periodical</genre> <genre>academic journal</genre> <titleInfo> <title>JVRB - Journal of Virtual Reality and Broadcasting</title> </titleInfo> <part> <detail type="volume"> <number>5(2008)</number> </detail> <detail type="issue"> <number>6</number> </detail> <date>2008</date> </part> </relatedItem> <identifier type="issn">1860-2037</identifier> <identifier type="urn">urn:nbn:de:0009-6-14446</identifier> <identifier type="doi">10.20385/1860-2037/5.2008.6</identifier> <identifier type="uri">http://nbn-resolving.de/urn:nbn:de:0009-6-14446</identifier> <identifier type="citekey">amjoun2008</identifier> </mods>Download
Full Metadata
Bibliographic Citation | JVRB, 5(2008), no. 6. |
---|---|
Title |
Predictive-DCT Coding for 3D Mesh Sequences Compression (eng) |
Author | Rachida Amjoun, Wolfgang Strasser |
Language | eng |
Abstract | This paper proposes a new compression algorithm for dynamic 3d meshes. In such a sequence of meshes, neighboring vertices have a strong tendency to behave similarly and the degree of dependencies between their locations in two successive frames is very large which can be efficiently exploited using a combination of Predictive and DCT coders (PDCT). Our strategy gathers mesh vertices of similar motions into clusters, establish a local coordinate frame (LCF) for each cluster and encodes frame by frame and each cluster separately. The vertices of each cluster have small variation over a time relative to the LCF. Therefore, the location of each new vertex is well predicted from its location in the previous frame relative to the LCF of its cluster. The difference between the original and the predicted local coordinates are then transformed into frequency domain using DCT. The resulting DCT coefficients are quantized and compressed with entropy coding. The original sequence of meshes can be reconstructed from only a few non-zero DCT coefficients without significant loss in visual quality. Experimental results show that our strategy outperforms or comes close to other coders. |
Subject | Animation, DCT, animated mesh compression, clustering, local coordinate frame, predictive coding |
Classified Subjects |
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DDC | 004 |
Rights | DPPL |
URN: | urn:nbn:de:0009-6-14446 |
DOI | https://doi.org/10.20385/1860-2037/5.2008.6 |