مشاهده مشخصات مقاله
Face recognition using Local Multi Dimensional Statistics
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نویسنده (ها) |
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Roghayeh Alemy
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Mohammad Ebrahim Shiri
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Farzad Didehvar
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Zaynab Hajimohammadi
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مربوط به کنفرانس |
چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران |
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چکیده |
Though numerous approaches have been proposed
for face recognition. In this paper we propose a novel
face recognition approach based on adaptively
weighted patch Local Statistic in Multi dimensional
(LMDS) when only one exemplar image per person is
available. In this approach, a face image is
decomposed into a set of equal-sized patches in a nonoverlapping
way. In order to obtain Local Multi
Dimensional Statistic Features in each patch, we
calculated mean and standard deviation of all pixels
along some directions. An adaptively weighting
scheme is used to assign proper weights to each
LMDS features to adjust the contribution of each
local area of a face in terms of the quantity of identity
information that a patch contains. An extensive
experimental investigation is conducted using AR face
databases covering face recognition under
controlled/ideal conditions and different facial
expressions. The system performance is compared
with the performance of four benchmark approaches.
The encouraging experimental results demonstrate
that our approach can be used for face recognition
and patch-based local statistic features provides a
novel way for face. |
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قیمت |
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برای اعضای سایت : ۱٠٠,٠٠٠ ریال
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برای دانشجویان عضو انجمن : ۲٠,٠٠٠ ریال
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برای اعضای عادی انجمن : ۴٠,٠٠٠ ریال
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