Robust photometric stereo via low-rank matrix completion and recovery

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6494 LNCS, Issue PART 3, 2011, Pages 703-717

  Wu, Lun ^a   Ganesh, Arvind ^b   Shi, Boxin ^d   Matsushita, Yasuyuki ^c   Wang, Yongtian ^a   Ma, Yi ^b,c  

^a BEIJING INSTITUTE OF TECHNOLOGY   (China)

^b University of Illinois at Urbana Champaign   (United States)

^c MICROSOFT RESEARCH ASIA   (China)

^d Peking University   (China)

Author keywords

[No Author keywords available]

Indexed keywords

CONVEX OPTIMIZATION TECHNIQUES; LAMBERTIAN; LEAST SQUARE; LIGHTING CONDITIONS; LOW-RANK MATRICES; NEW APPROACHES; PHOTOMETRIC STEREO; PHOTOMETRIC STEREO METHOD; ROBUST TECHNIQUE; SPECULARITIES; SURFACE NORMALS;

CONVEX OPTIMIZATION; FACE RECOGNITION; HEURISTIC METHODS; LEAST SQUARES APPROXIMATIONS; PHOTOMETRY; RECOVERY;

COMPUTER VISION;

EID: 79952528394     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-19318-7_55     Document Type: Conference Paper

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