Dynamic Hand Pose Recognition Using Depth Data
Hand pose recognition has been a problem of great interest to the Computer Vision and Human Computer Interaction community for many years and the current solutions either require additional accessories at the user end or enormous computation time. These limitations arise mainly due to the high dexte...
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| creator | Suryanarayan, Poonam Subramanian, Anbumani Mandalapu, Dinesh |
| description | Hand pose recognition has been a problem of great interest to the Computer Vision and Human Computer Interaction community for many years and the current solutions either require additional accessories at the user end or enormous computation time. These limitations arise mainly due to the high dexterity of human hand and occlusions created in the limited view of the camera. This work utilizes the depth information and a novel algorithm to recognize scale and rotation invariant hand poses dynamically. We have designed a volumetric shape descriptor enfolding the hand to generate a 3D cylindrical histogram and achieved robust pose recognition in real time. |
| doi_str_mv | 10.1109/ICPR.2010.760 |
| format | Conference Proceeding |
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We have designed a volumetric shape descriptor enfolding the hand to generate a 3D cylindrical histogram and achieved robust pose recognition in real time.</description><subject>Cameras</subject><subject>Depth Camera</subject><subject>Gesture</subject><subject>Principal component analysis</subject><subject>Real time systems</subject><subject>Shape</subject><subject>Shape Descriptor</subject><subject>SVM</subject><subject>Three dimensional displays</subject><subject>Thumb</subject><subject>Training</subject><issn>1051-4651</issn><issn>2831-7475</issn><isbn>1424475422</isbn><isbn>9781424475421</isbn><isbn>9781424475414</isbn><isbn>9780769541099</isbn><isbn>1424475414</isbn><isbn>0769541097</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1jE1Lw0AUANcvMNYcPXnZP5D43u57u9mjJNUWCpZSz2WTbOqCTUqTS_-9BfU0DAMjxBNCjgjuZVmuN7mCi1oDVyJ1tkBSRJYJ6VokqtCY2YveiIf_oNStSBAYMzKM9yIdx1iDMtZYZk5EXp17f4iNXPi-lethDHITmmHfxykOvfwcY7-XVThOX7Lyk38Ud53_HkP6x5nYvs235SJbfbwvy9dVFh1MmeVWUa2ZAjSh1g11xnYdO8uFV9h2ZAkBvdGd8-CsDtAaZGXAkG0dFnomnn-3MYSwO57iwZ_OO74cFGv9Ax3uRL8</recordid><startdate>201008</startdate><enddate>201008</enddate><creator>Suryanarayan, Poonam</creator><creator>Subramanian, Anbumani</creator><creator>Mandalapu, Dinesh</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201008</creationdate><title>Dynamic Hand Pose Recognition Using Depth Data</title><author>Suryanarayan, Poonam ; Subramanian, Anbumani ; Mandalapu, Dinesh</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-75d24b354e0ceb3c4f67ff59758a21df474101a63f9a0973e0d615260647d9183</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Cameras</topic><topic>Depth Camera</topic><topic>Gesture</topic><topic>Principal component analysis</topic><topic>Real time systems</topic><topic>Shape</topic><topic>Shape Descriptor</topic><topic>SVM</topic><topic>Three dimensional displays</topic><topic>Thumb</topic><topic>Training</topic><toplevel>online_resources</toplevel><creatorcontrib>Suryanarayan, Poonam</creatorcontrib><creatorcontrib>Subramanian, Anbumani</creatorcontrib><creatorcontrib>Mandalapu, Dinesh</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>IEEE Electronic Library (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>Suryanarayan, Poonam</au><au>Subramanian, Anbumani</au><au>Mandalapu, Dinesh</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Dynamic Hand Pose Recognition Using Depth Data</atitle><btitle>2010 20th International Conference on Pattern Recognition</btitle><stitle>ICPR</stitle><date>2010-08</date><risdate>2010</risdate><spage>3105</spage><epage>3108</epage><pages>3105-3108</pages><issn>1051-4651</issn><eissn>2831-7475</eissn><isbn>1424475422</isbn><isbn>9781424475421</isbn><eisbn>9781424475414</eisbn><eisbn>9780769541099</eisbn><eisbn>1424475414</eisbn><eisbn>0769541097</eisbn><abstract>Hand pose recognition has been a problem of great interest to the Computer Vision and Human Computer Interaction community for many years and the current solutions either require additional accessories at the user end or enormous computation time. These limitations arise mainly due to the high dexterity of human hand and occlusions created in the limited view of the camera. This work utilizes the depth information and a novel algorithm to recognize scale and rotation invariant hand poses dynamically. We have designed a volumetric shape descriptor enfolding the hand to generate a 3D cylindrical histogram and achieved robust pose recognition in real time.</abstract><pub>IEEE</pub><doi>10.1109/ICPR.2010.760</doi><tpages>4</tpages></addata></record> |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Cameras Depth Camera Gesture Principal component analysis Real time systems Shape Shape Descriptor SVM Three dimensional displays Thumb Training |
| title | Dynamic Hand Pose Recognition Using Depth Data |
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