Depth video enhancement for haptic interaction using a smooth surface reconstruction
Identifieur interne : 006112 ( Main/Curation ); précédent : 006111; suivant : 006113Depth video enhancement for haptic interaction using a smooth surface reconstruction
Auteurs : Seung-Man Kim [Corée du Sud] ; Jongeun Cha [Corée du Sud] ; Jeha Ryu [Corée du Sud] ; Kwan Heng Lee [Corée du Sud]Source :
- IEICE transactions on information and systems [ 0916-8532 ] ; 2006.
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Abstract
We present a depth video enhancement algorithm in order to provide high quality haptic interaction. As the telecommunication technology emerges rapidly, the depth image-based haptic interaction is becoming viable for broadcasting applications. Since a real depth map usually contains discrete and rugged noise, its haptic interaction produces the distorted force feedback. To resolve these problems, we propose a two-step refinement and adaptive sampling algorithm. In the first step, noise is removed by the median-filtering technique in 2D image space. Since not all pixels can be used to reconstruct the 3D mesh due to limited system resources, the filtered map is adaptively sampled based on the depth variation. Sampled 2D pixels, called feature points, are triangulated and projected onto 3D space. In the second refinement step, we apply the Gaussian smoothing technique to the reconstructed 3D surface. Finally, 3D surfaces are rendered to compute a smooth depth map from Z-buffer.
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Pascal:06-0226088Le document en format XML
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500-712</s2><s3>KOR</s3><sZ>2 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>Corée du Sud</country><wicri:noRegion>BukGu, Gwangju 500-712</wicri:noRegion></affiliation></author><author><name sortKey="Ryu, Jeha" sort="Ryu, Jeha" uniqKey="Ryu J" first="Jeha" last="Ryu">Jeha Ryu</name><affiliation wicri:level="1"><inist:fA14 i1="02"><s1>Human-Machine-Computer Interface Laboratory, Gwangju Institute of Science and Technology (GIST), 1 OryongDong</s1><s2>BukGu, Gwangju 500-712</s2><s3>KOR</s3><sZ>2 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>Corée du Sud</country><wicri:noRegion>BukGu, Gwangju 500-712</wicri:noRegion></affiliation></author><author><name sortKey="Lee, Kwan Heng" sort="Lee, Kwan Heng" uniqKey="Lee K" first="Kwan Heng" last="Lee">Kwan Heng Lee</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Intelligent Design and Graphics Laboratory, Gwangju Institute of Science and Technology (GIST)</s1><s3>KOR</s3><sZ>1 aut.</sZ><sZ>4 aut.</sZ></inist:fA14><country>Corée du 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first="Seung-Man" last="Kim">Seung-Man Kim</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Intelligent Design and Graphics Laboratory, Gwangju Institute of Science and Technology (GIST)</s1><s3>KOR</s3><sZ>1 aut.</sZ><sZ>4 aut.</sZ></inist:fA14><country>Corée du Sud</country><wicri:noRegion>Intelligent Design and Graphics Laboratory, Gwangju Institute of Science and Technology (GIST)</wicri:noRegion></affiliation></author><author><name sortKey="Cha, Jongeun" sort="Cha, Jongeun" uniqKey="Cha J" first="Jongeun" last="Cha">Jongeun Cha</name><affiliation wicri:level="1"><inist:fA14 i1="02"><s1>Human-Machine-Computer Interface Laboratory, Gwangju Institute of Science and Technology (GIST), 1 OryongDong</s1><s2>BukGu, Gwangju 500-712</s2><s3>KOR</s3><sZ>2 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>Corée du Sud</country><wicri:noRegion>BukGu, Gwangju 500-712</wicri:noRegion></affiliation></author><author><name sortKey="Ryu, Jeha" sort="Ryu, Jeha" uniqKey="Ryu J" first="Jeha" last="Ryu">Jeha Ryu</name><affiliation wicri:level="1"><inist:fA14 i1="02"><s1>Human-Machine-Computer Interface Laboratory, Gwangju Institute of Science and Technology (GIST), 1 OryongDong</s1><s2>BukGu, Gwangju 500-712</s2><s3>KOR</s3><sZ>2 aut.</sZ><sZ>3 aut.</sZ></inist:fA14><country>Corée du Sud</country><wicri:noRegion>BukGu, Gwangju 500-712</wicri:noRegion></affiliation></author><author><name sortKey="Lee, Kwan Heng" sort="Lee, Kwan Heng" uniqKey="Lee K" first="Kwan Heng" last="Lee">Kwan Heng Lee</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Intelligent Design and Graphics Laboratory, Gwangju Institute of Science and Technology (GIST)</s1><s3>KOR</s3><sZ>1 aut.</sZ><sZ>4 aut.</sZ></inist:fA14><country>Corée du Sud</country><wicri:noRegion>Intelligent Design and Graphics Laboratory, Gwangju Institute of Science and Technology (GIST)</wicri:noRegion></affiliation></author></analytic><series><title level="j" type="main">IEICE transactions on information and systems</title><title level="j" type="abbreviated">IEICE trans. inf. syst.</title><idno type="ISSN">0916-8532</idno><imprint><date when="2006">2006</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">IEICE transactions on information and systems</title><title level="j" type="abbreviated">IEICE trans. inf. syst.</title><idno type="ISSN">0916-8532</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adaptive method</term><term>Haptic interfaces</term><term>Image enhancement</term><term>Image reconstruction</term><term>Median filter</term><term>Noise reduction</term><term>Surface reconstruction</term><term>Tridimensional image</term><term>Video signal processing</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Traitement signal vidéo</term><term>Interface haptique</term><term>Accentuation image</term><term>Reconstruction surface</term><term>Reconstruction image</term><term>Image tridimensionnelle</term><term>Réduction bruit</term><term>Filtre médian</term><term>Méthode adaptative</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">We present a depth video enhancement algorithm in order to provide high quality haptic interaction. As the telecommunication technology emerges rapidly, the depth image-based haptic interaction is becoming viable for broadcasting applications. Since a real depth map usually contains discrete and rugged noise, its haptic interaction produces the distorted force feedback. To resolve these problems, we propose a two-step refinement and adaptive sampling algorithm. In the first step, noise is removed by the median-filtering technique in 2D image space. Since not all pixels can be used to reconstruct the 3D mesh due to limited system resources, the filtered map is adaptively sampled based on the depth variation. Sampled 2D pixels, called feature points, are triangulated and projected onto 3D space. In the second refinement step, we apply the Gaussian smoothing technique to the reconstructed 3D surface. Finally, 3D surfaces are rendered to compute a smooth depth map from Z-buffer.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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