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標題: | 產品開發之競爭策略研究–以微軟臉部辨識為例 Analyzing the Product Development and Competition Strategy of Microsoft Face Authentication Feature |
作者: | Yea-Hsin Chang 張逸昕 |
指導教授: | 曹承礎(Seng-Cho Chou) |
關鍵字: | 五力分析,價值網,賽局理論, Five-force Analysis,Value Net,Game Theory, |
出版年 : | 2016 |
學位: | 碩士 |
摘要: | 微軟臉部辨識為Windows 10推出的新功能,用使用者獨特的臉部影像作為數位憑證,代替密碼登入加密的系統。與之前作業系統比較,能創造產品差異化,增加升級的意願,且與雲端服務相結合,增加使用環境的安全性,創造Windows 10的價值。
臉部辨識需要特殊的紅外線攝影模組,因此新模組的被市場採用的程度可視為臉部辨識推展的程度。微軟希望臉部辨識功能與Windows 10的產品形象發揮綜效,但Windows 10推出一年之後臉部辨識的普及率卻不到1%。從微軟到模組廠商、到OEM、到終端使用者之間,模組的高成本造成生產速度緩慢、OEM持保留態度,使得此功能發展遲緩。 從價值網的觀點,為了讓臉部辨識與攝影模組的價值網活絡發展,在維持臉部辨識準確性與安全性的承諾之下,放寬硬體標準有助模組廠商降低進入門檻,擴大市場佔有率,等經濟規模建立再促使成本降低、品質提高,增加競爭力。研究產品設計的結果發現,對有限紅外線光源加以樽節,可以有效的降低成本且維持品質。光源最佳化的方式為縮短最遠距離限制、縮小視角及降低克服環境光上限等與實用性相關的項目。一旦實用性根據業界能力適度加以調整,硬體與臉部辨識功能從現今彩色攝影模組轉換時得到較低的轉換成本,臉部辨識功能可望得以普及。 Microsoft Face Authentication is a new feature of Windows 10, Human’s unique face pattern can be used as a digital certificate, be as an alternative solution of password, in order to sign-in protected systems. By comparing with previous OS version, it brings up product differentiation to users, and may activate their upgrade motivation. Furthermore, this feature works with cloud services by two-factor authentication, is another security enhancement feature. Face Authentication is required to work with specific IR camera design, therefore the marketing share of IR camera modules can represent the scale-out status of the feature. Microsoft expects that Face Authentication will create synergy with Windows 10 product marketing image. However, the marketing share is less than 1% in Windows launch anniversary. The combination of Value Net study shows the path of Microsoft, Module Makers, OEMs and end-users went non-efficiently; the high cost of module causes slow production, and OEMs are hesitated for the feature adoption. To enable IR camera module and Face Authentication ecosystem, by security and accuracy quality bar remaining high, it is possible to extend the marketing share by cost redundant, where the specification of hardware requirement be leveraged by reasonable adjustment, like far distance, FOV, ambient light bar, etc. When the switching costs are acceptable from RGB camera to RGB-IR camera, it is easier to scale-out the Face Authentication module adoption and win the market in the future. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/50045 |
DOI: | 10.6342/NTU201601843 |
全文授權: | 有償授權 |
顯示於系所單位: | 資訊管理組 |
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