Automatic Face Recognition ( AFR ) is challenging in image processing and analyzing.
自動人臉識別技術(shù) ( AFR ) 是一項極具挑戰(zhàn)性的前沿研究課題.
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In addition, elaborate system design is also as important for developing robust and practical AFR systems.
另外,對開發(fā)魯棒實用的AFR系統(tǒng) 而言, 研究應(yīng)用系統(tǒng)設(shè)計層面的諸多工程技術(shù)問題同樣至關(guān)重要.
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In this thesis, the above - mentioned key issues are studied , aiming at robust and practical AFR systems.
以設(shè)計開發(fā)魯棒、實用的AFR系統(tǒng)為目標(biāo),本文重點探討了人臉識別中的上述關(guān)鍵問題.
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Model based AFR control strategy requires accurate engine model first.
基于模型的空燃比控制策略首先要求有精確的模型,均值模型是非線性模型,其精度高、表達(dá)形式簡單,能夠滿足控制過程實時性的要求,是比較理想的模型.
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Based on the traditional eigenfaces method, this paper presents an improving approach to AFR.
在傳統(tǒng)的“特征臉”方法基礎(chǔ)上, 提出了一種改進的人臉自動識別方法.
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However, evaluation results and practical experience have shown that AFR technologies are currently far from mature.
但測試和實踐經(jīng)驗表明:非理想條件下的人臉識別技術(shù)還遠(yuǎn)未成熟!
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