性別是人類一項重要的特徵，一個自動且有效的性別辨識系統，可以廣泛的應用在安全監控、人機介面或消費者行為分析等領域，例如在消費者行為分析方面，將數位廣告看板加上性別辨識系統，根據不同的性別播放不同的廣告，以吸引更多潛在的顧客。

不同性別之間的人臉外觀有顯著的差異，因此利用人臉特徵來判斷性別是最直覺的方法，近年來，許多利用人臉與五官特徵來辨識性別的方法相繼被提出，但是在真實的環境中，路上的行人經常會有像是戴墨鏡或是圍圍巾的裝扮，這些人臉部分遮蔽的情形可能導致辨識率下降，因此本論文提出一個適應型的性別辨識方法，首先在遮蔽分類的階段偵測出被遮蔽的五官區塊，然後只選擇未遮蔽的區塊來辨識性別，利用這種動態選擇五官區塊的方式來解決因部分遮蔽所造成的誤判並且提升整體的辨識率。

實驗方面，從三個部分來探討，分別是各區塊的性別辨識結果、綜合各區塊辨識結果的適應型性別辨識以及利用部分遮蔽影像來測試系統的強健性，實驗結果顯示，在未遮蔽或有部分遮蔽的人臉影像中，本論文提出的性別辨識方法皆能維持良好的辨識率。

Gender is a very important personal attribute inherent in human beings. Hence, an automatic and effective gender recognition system is desirable in various applications, such as intelligent surveillance system, human-computer interaction, and customer behavior analysis. Take customer behavior analysis for example, the applying of gender recognition technology in digital signage can attract potential customers while demonstrating custom advertisements.

Since human face conveys a clear sexual dimorphism, the using of facial features seems to be an intuitive way for gender recognition. In consequence, abundant gender recognition methods were proposed based on certain facial components. However, people may wear sunglasses or scarves in real life which will result in occluded facial image. Under these circumstances, the performance of gender recognition will thus be degraded due to the occlusion problem. In this thesis, we propose an adaptive gender recognition method by dynamically selecting facial components to cope with the aforementioned problem. In the occlusion classification procedure, the occluded facial components are firstly detected and only the non-occluded facial components are selected in the recognition role to overcome the failure problem suffering the recognition performance.

Three different experiments were conducted to verify the validity of our proposed method. They were categorized in terms of single classifier of components, multiple classifiers for adaptive gender recognition, and system robustness test by using partial occlusion image. Experimental results demonstrate that the proposed method exhibit excel accuracy under various conditions.

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