Pose estimation of a human arm using kinematic constraints

Thispaperis concernedwith visualmotioncaptureof ahumanarm. Theinput is a colour imageandtheoutputis the 3D poseof thearmin thecurrentimage.To handletheobvious ambiguitiesinvolved in 3D estimationbasedon 2D dataa model-basedapproachis adaptedwhereall configurationsof thearmarematchedwith the imagedata.These configurationsareefficiently foundthrougha compactrepresentationof themodelof thearmtogetherwith kinematic constraints.Therepresentationis obtainedby exploiting the geometryof thearmtogetherwith imagemeasurements of the positionof the hand. It turnsout that two parameters aresufficient to representhe3D poseof thearm.Theseparametersareprunedusingkinematicconstraints.Theconstraintsaredefinedfrom thelengthof theupperandlower arms,togetherwith thelimits on thefour joint anglesof the arm. Altogetherthe compactrepresentationand the constraintsreducethe numberof configurationssignificantly andthereforeallows for anexhausti vematchingprocedure. Themethodis testedin amodel-basedsilhouetteframework andtestsshow promisingresults.

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