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frequency-division-multiplexing based period-coded fringe pattern for reliable depth sensing
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نویسنده
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yang l. ,li f. ,shi g. ,li r. ,niu y. ,gao z. ,dou p.
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منبع
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journal of the european optical society-rapid publications - 2018 - دوره : 14 - شماره : 1
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چکیده
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The fringe pattern can realize high-resolution and dense depth sensing. however, the phase ambiguity is a challenge in the fringe pattern. in this paper, one period-code pattern is embedded to the fringe pattern by the frequency-division-multiplexing (fdm) framework. the nonparametric skew and de bruijn sequence are utilized to determine the label of the period. for a more reliable phase unwrapping, three criteria are utilized to rectify the period numbers further. quantitative and qualitative experiments show that the proposed method can achieve more reliable depth sensing compared with the counterparts. even the measured scene contains discontinuous surfaces or sharp edges, the proposed algorithm can attain reliable depth. © 2018, the author(s).
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کلیدواژه
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depth sensing ,fringe pattern ,range sensing ,single-shot pattern ,structured light
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آدرس
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chinese ministry of education, xidian university, school of artificial intelligence, key laboratory of intelligent perception and image understanding, china, chinese ministry of education, xidian university, school of artificial intelligence, key laboratory of intelligent perception and image understanding, china, chinese ministry of education, xidian university, school of artificial intelligence, key laboratory of intelligent perception and image understanding, china, chinese ministry of education, xidian university, school of artificial intelligence, key laboratory of intelligent perception and image understanding, china, chinese ministry of education, xidian university, school of artificial intelligence, key laboratory of intelligent perception and image understanding, china, chinese ministry of education, xidian university, school of artificial intelligence, key laboratory of intelligent perception and image understanding, china, chinese ministry of education, xidian university, school of artificial intelligence, key laboratory of intelligent perception and image understanding, china
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Authors
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