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Rachida Amjoun, and Wolfgang Strasser, PredictiveDCT Coding for 3D Mesh Sequences Compression. JVRB  Journal of Virtual Reality and Broadcasting, 5(2008), no. 6. (urn:nbn:de:0009614446)
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%0 Journal Article %T PredictiveDCT 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 %@ 18602037 %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 nonzero 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 10.20385/18602037/5.2008.6 %U http://nbnresolving.de/urn:nbn:de:0009614446 %U http://dx.doi.org/10.20385/18602037/5.2008.6Download
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@Article{amjoun2008, author = "Amjoun, Rachida and Strasser, Wolfgang", title = "PredictiveDCT 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 nonzero DCT coefficients without significant loss in visual quality. Experimental results show that our strategy outperforms or comes close to other coders.", issn = "18602037", doi = "10.20385/18602037/5.2008.6", url = "http://nbnresolving.de/urn:nbn:de:0009614446" }Download
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TY  JOUR AU  Amjoun, Rachida AU  Strasser, Wolfgang PY  2008 DA  2008// TI  PredictiveDCT 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 nonzero DCT coefficients without significant loss in visual quality. Experimental results show that our strategy outperforms or comes close to other coders. SN  18602037 UR  http://nbnresolving.de/urn:nbn:de:0009614446 DO  10.20385/18602037/5.2008.6 ID  amjoun2008 ER Download
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<?xml version="1.0" encoding="UTF8"?> <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://nbnresolving.de/urn:nbn:de:0009614446</b:Url> <b:Url>http://dx.doi.org/10.20385/18602037/5.2008.6</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>PredictiveDCT 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 nonzero 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 PredictiveDCT Coding for 3D Mesh Sequences Compression SO JVRB  Journal of Virtual Reality and Broadcasting PY 2008 VL 5(2008) IS 6 DI 10.20385/18602037/5.2008.6 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 nonzero DCT coefficients without significant loss in visual quality. Experimental results show that our strategy outperforms or comes close to other coders. ERDownload
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<mods> <titleInfo> <title>PredictiveDCT 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 nonzero 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">18602037</identifier> <identifier type="urn">urn:nbn:de:0009614446</identifier> <identifier type="doi">10.20385/18602037/5.2008.6</identifier> <identifier type="uri">http://nbnresolving.de/urn:nbn:de:0009614446</identifier> <identifier type="citekey">amjoun2008</identifier> </mods>Download
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Bibliographic Citation  JVRB, 5(2008), no. 6. 

Title 
PredictiveDCT 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 nonzero 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 

DDC  004 
Rights  DPPL 
URN:  urn:nbn:de:0009614446 
DOI  https://doi.org/10.20385/18602037/5.2008.6 