人臉辨識一般而言可分為識別及驗證等兩種應用情境。早期的人臉辨識輸入資料，大多是透過二維灰階或彩色影像。同時，有一部分的研究工作，亦引入立體視覺系統作為人臉辨識的資料輸入。隨著感測器的進步與發展，越來越多的深度量測儀器，被用來取得三維的臉部資訊，作為人臉辨識的資料輸入。一般而言，二維臉部資料較易受到環境光源、臉部方位、及彩妝等影響而造成準確性下滑，因此常受到使用環境上的諸多限制。而三維資料雖可克服上述缺點，但仍有高運算量及易受臉部表情影響等限制。因此，結合兩者的優點，以實現一個實用且穩定的人臉辨識技術，為一個目前引起高度研究興趣的新課題。本論文將對目前該領域的研究，作一詳盡的介紹與比較，相信能對建基於多維資訊的現代人臉辨識系統的發展有所助益。

The application of face recognition technology generally focuses on two scenarios including identification and validation. Conventional approaches use 2D intensity or color images, and some approaches introduce stereovision system to acquire 3D information for the recognition process. In general, 2D based approaches suffer from severe problems related to environmental conditions, such as variation of ambient light, occlusion due to face orientation and costume, etc. On the other hand, 3D based ones have to overcome the challenge of computational cost and expression variation, though some of the previous 2D problems can be avoided. As the depth sensor technology is being improved, more and more depth measurement equipments are utilized to generate 3D data, particularly the depth of the facial object, for numerous systems. The integration and combination of these two spectrums is thus now a very active research interest, which aims to construct a reliable and efficient face recognition system. The purpose of this paper is to provide a comprehensive survey of the proposed methods in this area and a comparison among them, in order to yield fundamental basis for future developments of a practical face recognition system.