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+or+shape-from-polarization+(SfP)%252C+rely+on+strong+assumptions+about+the+measured+objects%252C+limiting+their+generalizability+in+broader+application+areas+like+medical+imaging%252C+industrial+inspection%252C+virtual+reality%252C+or+cultural+heritage+analysis.+In+this+paper%252C+we+introduce+a+measurement+principle+that+utilizes+a+novel+technique+to+effectively+encode+and+decode+the+information+contained+in+a+light+field+reflected+off+a+specular+surface.+We+combine+polarization+cues+from+SfP+with+geometric+information+obtained+from+PMD+to+resolve+all+arising+ambiguities+in+the+3D+measurement.+Moreover%252C+our+approach+removes+the+unrealistic+orthographic+imaging+assumption+for+SfP%252C+which+significantly+improves+the+respective+results.+We+showcase+our+new+technique+by+demonstrating+single-shot+and+multi-shot+measurements+on+complex-shaped+specular+surfaces%252C+displaying+an+evaluated+accuracy+of+surface+normals+below+%25240.6%5ecirc%2524.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.cbd008dcecddcc498dd2134cda867a30%3frik%3deyaFEtwFwa1SLQ%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=Specular+Model&FORM=IRPRST&ck=78F54B7295F70FD130C458CC3D105B96&selectedIndex=10&itb=0)
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