TW202036437A - Financial planning system with face recognition function including an image input terminal, a server host, and a display device connected in signals by virtue of a router - Google Patents
Financial planning system with face recognition function including an image input terminal, a server host, and a display device connected in signals by virtue of a router Download PDFInfo
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Description
本發明涉及金融理財規劃設備的技術領域，尤其涉及一種金融理財規劃系統，能經由人臉辨識即可快速提供理財規劃結果，以做為理財投資參考。 The present invention relates to the technical field of financial management planning equipment, in particular to a financial management planning system, which can quickly provide financial planning results through face recognition, which can be used as a reference for financial management investment.
隨著資訊科技突飛猛進，人們對於即時且方便的資訊取得與通訊需求更是呈現***性的成長，而對於金融理財方面的資訊的需求也有越來越提昇的趨勢。 With the rapid advancement of information technology, people's demand for instant and convenient information acquisition and communication is showing explosive growth, and the demand for financial management information is also increasing.
目前，在金融機構內的理財顧問，大都依靠該金融機構內的電腦主機及內部的資訊伺服器的資訊管理系統來進行客戶管理，並據以向客戶提供理財服務產品；對於個人理財顧問來說，一般亦係利用個人電腦的資訊庫或試算表程式來進行理財建議服務。 At present, financial consultants in financial institutions mostly rely on the information management system of the computer host and internal information server in the financial institution to manage customers, and provide financial service products to customers accordingly; for personal financial consultants , Generally also use personal computer information database or spreadsheet program to provide financial advice services.
如中華民國公告第M564785號之「理財建議伺服器」專利案、申請第105115441號之「理財保險試算工具系統、方法及其電腦程式產品」專利案、申請第106100122號之「智慧型理財管理系統」專利案、申請第093123834號之「理財規劃服務系統及其方法」專利案。 For example, the Republic of China Announcement No. M564785 of the "Financial Management Advice Server" patent case, Application No. 105115441 of the "Financial Management Insurance Trial Calculation Tool System, Method and Computer Program Products" patent case, Application No. 106100122 of the "Smart Financial Management System" "Patent case, application No. 093123834 "Financial planning service system and its method" patent case.
然而，由於這些電腦及伺服器的資訊管理系統、資訊庫或試算表程式等都是封閉式系統，理財顧問只依靠封閉的系統提供的固定運作 模式來進行金融理財建議的服務，所提供的建議內容難免侷限。 However, since the information management systems, information databases or spreadsheet programs of these computers and servers are all closed systems, financial advisors only rely on the fixed operations provided by the closed systems Mode to provide financial advice services, the advice provided is inevitably limited.
而投資人的財務行為(Behaviral Finance)才是真正影響投資人是否獲利的關鍵因素，根據國外研究顯示透過視覺資料來向投資人展示更能有效幫助其正確的財務行為。 The financial behavior of investors (Behaviral Finance) is the key factor that really affects whether investors are profitable. According to foreign research, it is more effective to show investors correct financial behaviors through visual data.
本發明之主要目的，在針對金融理財方面的分析與建議提供另一種不同的操作系統，讓使用者經由人臉辨識即可快速提供理財規劃結果，以做為理財投資參考。 The main purpose of the present invention is to provide another different operating system for analysis and suggestions in financial management, so that users can quickly provide financial planning results through face recognition, which can be used as a reference for financial investment.
為了達成上述之目的與功效，本發明人臉辨識金融理財規劃系統，包括透過一路由器進行訊號聯結的一影像輸入端、一伺服器主機以及一顯示設備：該影像輸入端透過路由器傳送一臉部影像至該伺服器主機。 In order to achieve the above-mentioned purposes and effects, the face recognition financial planning system of the present invention includes an image input terminal, a server host and a display device that are signaled through a router: the image input terminal transmits a face through the router Image to the server host.
該伺服器主機包含訊號聯結的一人臉特徵資料集、一人臉辨識模組及一理財分析模組，該人臉特徵資料集透過程式建立年齡、性別與情緒規則，且該人臉辨識模組透過該臉部影像取得一臉部影像輪廓輸入、臉部影像特徵輸入的資料時，使人臉辨識模組分析該臉部影像並產生一匯出資料，且該匯出資料包含一年齡資料、一性別資料及一情緒資料，該理財分析模組根據該年齡資料、性別資料及情緒資料進行一投資金額計算演算、一投資人類型評估演算以及一投資組合計算演算以產生一理財規劃結果，該理財規劃結果包含該投資金額計算演算產生的一投資金額、該投資人類型評估演算所產的一投資人類型，以及該投資組合計算演算所產生的一投資組合圖式。 The server host includes a face feature data set, a face recognition module, and a financial analysis module that are signal-connected. The face feature data set is programmed to establish age, gender and emotion rules, and the face recognition module passes When the facial image obtains the data of a facial image contour input and a facial image feature input, the face recognition module is made to analyze the facial image and generate an exported data, and the exported data includes an age data, an Gender data and emotional data. The financial analysis module performs an investment amount calculation calculation, an investor type evaluation calculation, and an investment portfolio calculation calculation based on the age data, gender data, and emotional data to generate a financial planning result. The planning result includes an investment amount generated by the investment amount calculation calculation, an investor type generated by the investor type evaluation calculation, and an investment portfolio schema generated by the investment portfolio calculation calculation.
該顯示設備顯示該理財規劃結果提供參考。 The display device displays the results of the financial planning to provide reference.
本發明進一步的技術特徵在於，該投資金額計算演算係依取得臉部影像的年齡資料，利用利用政府統計各年齡層收入分佈數據，依建議投資比例計算出該投資金額。 A further technical feature of the present invention is that the investment amount calculation calculation is based on the age data of the acquired facial images, using government statistics on income distribution data of each age group, and calculating the investment amount according to the recommended investment ratio.
本發明進一步的技術特徵在於，該投資人類型評估演算係依取得臉部影像的年齡資料、性別資料及情緒資料後，評估風險等級可能為30~100之間，每5為單位，依投資可承受風險值，以歸類該臉部影像所屬之投資人類型可能屬於謹慎保守型、意見追隨者型、累積財富積極型與個人主義大師型其中之一。 A further technical feature of the present invention is that the investor type evaluation algorithm is based on the age data, gender data, and emotion data of the facial image. The evaluation risk level may be between 30 and 100, with every 5 as the unit, depending on the investment. The risk value to classify the type of investor to which the facial image belongs may be one of the cautious and conservative type, the opinion follower type, the positive wealth accumulation type, and the individualist master type.
本發明進一步的技術特徵在於，該投資組合計算演算依取得該臉部影像年齡的年齡資料後，利用風險等級配置投資組合，依效率前緣(Effecient Frontier)計算出一投資內容組合比例，並產生該投資組合圖式。 A further technical feature of the present invention is that the investment portfolio calculation algorithm uses the risk level to configure the investment portfolio after obtaining the age data of the facial image age, and calculates an investment content portfolio ratio based on the Effecient Frontier, and generates The portfolio schema.
本發明進一步的技術特徵在於，該理財分析模組進一步進行一退休規劃演算，係取得該臉部影像的年齡資料、性別資料及情緒資料後，政府統計每人每月消費支出數據，計算出退休後總花費，依蒙地卡羅(Monte Carlo)方法模擬1萬次市場投資情況，推算出一投資金額，於退休時得到足夠的資產，以滿足退休後的花費。 A further technical feature of the present invention is that the financial analysis module further performs a retirement planning calculation. After obtaining the age data, gender data and emotional data of the facial image, the government counts the monthly consumption expenditure data per person to calculate retirement After the total expenditure, according to the Monte Carlo (Monte Carlo) method to simulate 10,000 times of market investment, calculate an investment amount, and get enough assets at retirement to meet the expenditure after retirement.
本發明進一步的技術特徵在於，該理財分析模組進一步進行一保險計算演算，係取得該臉部影像的年齡資料、性別資料後，依不同性別、在不同年齡層所屬不同人生階段的需求數據，針對壽險、意外險、產險、醫療險與重大疾病險規劃保障內容，依保險費用比例計算出建議投 保金額，並分配於規劃的保險中。 A further technical feature of the present invention is that the financial analysis module further performs an insurance calculation calculation to obtain the age data and gender data of the facial image, according to the demand data of different genders and different life stages in different age groups. For life insurance, accident insurance, property insurance, medical insurance and critical illness insurance plan coverage, the recommended investment is calculated based on the proportion of insurance costs The insured amount is allocated to the planned insurance.
本發明進一步的技術特徵在於，該理財分析模組進一步進行一貸款計算演算，係取得該臉部影像的年齡資料後，利用利用政府統計各年齡層收入分佈數據，依預估財力計算出可貸款金額。 A further technical feature of the present invention is that the financial analysis module further performs a loan calculation calculation, which is to obtain the age data of the facial image and use the government to calculate the income distribution data of each age group to calculate the loanable according to the estimated financial strength Amount.
本發明進一步的技術特徵在於，該影像輸入端傳送的臉部影像為透過一網路攝影機所擷取自一規劃對像的人臉。 A further technical feature of the present invention is that the facial image transmitted by the image input terminal is a human face captured from a planned object through a webcam.
本發明進一步的技術特徵在於，該影像輸入端傳送的該臉部影像為取自安裝有應用程式的手機/電腦所上傳的照片。 A further technical feature of the present invention is that the facial image sent by the image input terminal is a photo taken from a mobile phone/computer with an application installed.
(10)‧‧‧影像輸入端 (10)‧‧‧Video input terminal
(11)‧‧‧臉部影像 (11)‧‧‧Face image
(20)‧‧‧伺服器主機 (20)‧‧‧Server Host
(21)‧‧‧人臉特徵資料集 (21)‧‧‧Face feature dataset
(22)‧‧‧人臉辨識模組 (22)‧‧‧Face recognition module
(221)‧‧‧臉部影像輪廓輸入 (221)‧‧‧Face image contour input
(222)‧‧‧臉部影像特徵輸入 (222)‧‧‧Face image feature input
(23)‧‧‧理財分析模組 (23)‧‧‧Financial Analysis Module
(231)‧‧‧投資金額計算演算 (231)‧‧‧Calculation of investment amount
(2311)‧‧‧投資金額 (2311)‧‧‧Investment amount
(232)‧‧‧投資人類型評估演算 (232)‧‧‧Investor Type Evaluation Calculation
(2321)‧‧‧投資人類型 (2321)‧‧‧Type of investor
(233)‧‧‧投資組合計算演算 (233)‧‧‧Investment portfolio calculation calculation
(2331)‧‧‧投資組合圖式 (2331)‧‧‧ Portfolio Schema
(234)‧‧‧退休規劃演算 (234)‧‧‧Retirement planning calculation
(235)‧‧‧保險計算演算 (235)‧‧‧Insurance calculation calculation
(236)‧‧‧貸款計算演算 (236)‧‧‧Loan calculation calculation
(30)‧‧‧顯示設備 (30)‧‧‧Display equipment
(40)‧‧‧路由器 (40)‧‧‧ Router
(50)‧‧‧規劃對像 (50)‧‧‧Planning target
(A)‧‧‧深度學習模型 (A)‧‧‧Deep learning model
(B)‧‧‧深度學習規則 (B)‧‧‧Deep learning rules
(C)‧‧‧且該匯出資料 (C)‧‧‧and the data should be exported
(C1)‧‧‧年齡資料 (C1)‧‧‧Age Information
(C2)‧‧‧性別資料 (C2)‧‧‧Gender information
(C3)‧‧‧情緒資料 (C3)‧‧‧Mood data
(D)‧‧‧理財規劃結果 (D)‧‧‧Financial Planning Results
(E)‧‧‧判斷精準度 (E)‧‧‧Judgment accuracy
第一圖為本發明之設備方塊示意圖。 The first figure is a block diagram of the device of the present invention.
第二圖為本發明的深度學習測試階段示意圖。 The second figure is a schematic diagram of the deep learning test stage of the present invention.
第三圖為本發明的深度學習執行階段示意圖。 The third figure is a schematic diagram of the deep learning execution stage of the present invention.
第四圖為本發明理財分析模組的理財分析運算示意圖。 The fourth figure is a schematic diagram of the financial analysis operation of the financial analysis module of the present invention.
第五圖為本發明之理財規劃結果平面示意圖。 The fifth figure is a schematic diagram of the result of the financial planning of the present invention.
第六圖為本發明使用狀態示意圖。 The sixth figure is a schematic diagram of the state of use of the present invention.
本發明為達成上述的目的與功效，以及所採用之技術手段與構造，茲搭配圖示就本發明的實施例加以詳細說明其特徵與功效。 In order to achieve the above-mentioned objectives and effects, as well as the technical means and structures adopted by the present invention, the features and effects of the embodiments of the present invention are described in detail with the figures.
請參閱第一至六圖所示本發明一種人臉辨識金融理財規劃系統：包括透過一路由器(40)進行訊號聯結的一影像輸入端(10)、一伺服器主機(20)以及一顯示設備(30)： 該影像輸入端(10)透過路由器(40)傳送一臉部影像(11)至該伺服器主機(20)。 Please refer to Figures 1 to 6 showing a face recognition financial planning system of the present invention: including an image input terminal (10), a server host (20) and a display device for signal connection through a router (40) (30): The image input terminal (10) transmits a face image (11) to the server host (20) through the router (40).
該伺服器主機(20)包含訊號聯結的一人臉特徵資料集(21)、一人臉辨識模組(22)及一理財分析模組(23)，該人臉特徵資料集(21)透過程式建立年齡、性別與情緒規則，且該人臉辨識模組(22)透過該臉部影像(11)取得一臉部影像輪廓輸入(221)、臉部影像特徵輸入(222)的資料時，使人臉辨識模組(22)分析該臉部影像(11)並產生一匯出資料(C)，且該匯出資料(C)包含一年齡資料(C1)、一性別資料(C2)及一情緒資料(C3)，該理財分析模組(23)根據該年齡資料(C1)、性別資料(C2)及情緒資料(C3)進行一投資金額計算演算(231)、一投資人類型評估演算(232)以及一投資組合計算演算(233)以產生一理財規劃結果(D)，該理財規劃結果(D)包含該投資金額計算演算(231)產生的一投資金額(2311)、該投資人類型評估演算(232)所產的一投資人類型(2321)，以及該投資組合計算演算(233)所產生的一投資組合圖式(2331)。 The server host (20) includes a face feature data set (21), a face recognition module (22) and a financial analysis module (23) connected by signals. The face feature data set (21) is created through a program Age, gender and emotion rules, and the face recognition module (22) obtains the data of a facial image contour input (221) and facial image feature input (222) through the facial image (11). The face recognition module (22) analyzes the face image (11) and generates an exported data (C), and the exported data (C) includes an age data (C1), a gender data (C2) and an emotion Data (C3), the financial analysis module (23) performs an investment amount calculation calculation (231) and an investor type evaluation calculation (232) based on the age data (C1), gender data (C2) and emotional data (C3) ) And an investment portfolio calculation calculation (233) to produce a financial planning result (D), the financial planning result (D) includes an investment amount (2311) generated by the investment amount calculation calculation (231), and the investor type assessment An investor type (2321) produced by the calculation (232), and an investment portfolio schema (2331) produced by the calculation (233) of the investment portfolio.
該顯示設備(30)顯示該理財規劃結果(D)提供該參考。 The display device (30) displays the financial planning result (D) to provide the reference.
前述為本發明主實施例之主要技術特徵，其對應本案申請專利範圍第一項的內容，得以詳知本發明之目的與實施型態，而其餘附屬申請專利範圍所述的技術特徵是為對申請專利範圍第一項內容的詳述或附加技術特徵，而非用以限制申請專利範圍第一項的界定範圍，應知本案申請專利範圍第一項不必要一定包含其餘附屬申請專利範圍所述的技術特徵。 The foregoing are the main technical features of the main embodiment of the present invention, which correspond to the content of the first item of the patent application in this case, so that the purpose and implementation mode of the present invention can be known in detail, while the technical features described in the other subsidiary patent applications are for The detailed description or additional technical features of the first item of the scope of patent application are not used to limit the scope of the first item of the scope of patent application. It should be understood that the first item of the scope of patent application in this case does not necessarily include the scope of the remaining subsidiary patent applications. Technical characteristics.
於下進一步細述本發明的各元件之特徵，在上述第一 至六圖中，該投資金額計算演算(231)係依取得臉部影像(11)的年齡資料(C1)，利用政府統計各年齡層收入分佈數據(如透過網路取得行政院主計處按年齡分收入統計數據進行比對)，依建議投資比例計算出該投資金額(2311)。其次，該投資人類型評估演算(232)係依取得臉部影像(11)的年齡資料(C1)、性別資料(C2)及情緒資料(C3)後，評估風險等級可能為30~100之間，每5為單位，依投資可承受風險值，以歸類該臉部影像(11)所屬之投資人類型(2321)可能屬於謹慎保守型、意見追隨者型、累積財富積極型與個人主義大師型其中之一。再者，該投資組合計算演算(233)依取得該臉部影像(11)年齡的年齡資料(C1)後，利用風險等級配置最適的投資組合，依效率前緣(Effecient Frontier)計算出最佳的一投資內容組合比例，並產生該投資組合圖式(2331)。 The features of each element of the present invention are further described below. In the first In Figure 6, the calculation of the investment amount (231) is based on the age data (C1) obtained from the facial image (11), using government statistics on the income distribution of various age groups (such as the Internet Compare by income statistics), calculate the investment amount according to the recommended investment ratio (2311). Secondly, the investor type evaluation algorithm (232) is based on the age data (C1), gender data (C2) and emotion data (C3) obtained from the facial image (11), and the risk level may be between 30 and 100. , Every 5 units, according to the risk value of the investment, to classify the type of investor (2321) to which the facial image (11) belongs. It may be a cautious and conservative type, an opinion follower type, an active wealth accumulation type and a master of individualism Type one of them. Furthermore, the portfolio calculation calculation (233) uses the risk level to configure the most suitable portfolio after obtaining the age data (C1) of the facial image (11) age, and calculates the best based on the Effecient Frontier An investment content portfolio ratio of, and generate the portfolio schema (2331).
如第一、六圖所示，該影像輸入端(10)傳送的臉部影像(11)為透過一網路攝影機所擷取自一規劃對像(50)的人臉。 As shown in the first and sixth figures, the face image (11) sent by the image input terminal (10) is a face captured from a planning target (50) through a webcam.
在第二圖的深度學習模型(A)之操作中，將網路攝影機設置於往來人員眾多的大廳或場所中，用以擷取經過網路攝影機前的人員臉部影像(11)進行學習，配合問卷取得對應臉部影像(11)的該人員年齡、性別資料，由於該人臉特徵資料集(21)透過程式建立年齡、性別與情緒規則，例如縐紋多寡與深度與年齡大小關係、頭髮長度、形狀特徵與性別關係，及嘴角上揚幅度與情緒的關係，使人臉辨識模組(22)得以藉由一臉部影像輪廓輸入(221)、一臉部影像特徵輸入(222)的資料與人臉特徵資料集(21)的比對進行深度學習模型(A)的操作，透過核對於由問卷取得對應臉部影像(11)的人員年齡、性別資料所進行一判斷精準度(E)的測試操作中，學習該人臉特徵 資料集(21)的規則，於測試不準確時沿圖中箭頭所示重新進行正確學習，能據以累積判斷準確的經驗值而建立一深度學習規則(B)。 In the operation of the deep learning model (A) in the second figure, the network camera is set up in a hall or place with many people passing by to capture the facial image (11) of the person passing by the network camera for learning. Cooperate with the questionnaire to obtain the person’s age and gender data corresponding to the facial image (11). Because the facial feature data set (21) is programmed to establish age, gender and emotional rules, such as the amount and depth of crepe and the relationship between age and hair The relationship between length, shape characteristics and gender, as well as the relationship between the height of the mouth and emotions, enables the face recognition module (22) to input data from a facial image contour input (221) and a facial image feature input (222) Comparing with the face feature data set (21), perform the operation of the deep learning model (A), and make a judgment accuracy (E) on the age and gender data of the person corresponding to the face image (11) obtained from the questionnaire. In the test operation, learn the facial features The rules of the data set (21) are re-learned correctly along the arrow shown in the figure when the test is not accurate, and a deep learning rule (B) can be established based on the accumulated experience value for judging the accuracy.
接著於第三圖的深度學習執行階段中，於該網路攝影機擷取一臉部影像(11)，並使人臉辨識模組(22)透過該臉部影像(11)接收一臉部影像輪廓輸入(221)、臉部影像特徵輸入(222)的資料時，使人臉辨識模組(22)藉由建立的該深度學習規則(B)分析該臉部影像(11)的臉部影像輪廓輸入(221)、臉部影像特徵輸入(222)資料，得以產生包含一年齡資料(C1)、一性別資料(C2)及一情緒資料(C3)的一匯出資料(C)；進而如第四圖所示，該匯出資料(C)提供理財分析模組(23)進行該投資金額計算演算(231)時以產生一投資金額(2311)、進行投資人類型評估演算(232)時以產的一投資人類型(2321)，以及進行該投資組合計算演算(233)時以產生的一投資組合圖式(2331)，如第五、六圖所示。 Then in the deep learning execution stage of the third figure, a facial image (11) is captured from the webcam, and the face recognition module (22) receives a facial image through the facial image (11) When the contour input (221) and the facial image feature input (222) data, the face recognition module (22) is made to analyze the facial image of the facial image (11) by the established deep learning rule (B) Contour input (221) and facial image feature input (222) data can generate an export data (C) including an age data (C1), a gender data (C2), and an emotion data (C3); As shown in the fourth figure, when the exported data (C) is provided with the financial analysis module (23) for the calculation of the investment amount (231) to generate an investment amount (2311), when the investor type evaluation calculation (232) is performed An investor type (2321) of the property, and an investment portfolio schema (2331) generated when the investment portfolio calculation calculation (233) is performed, as shown in Figures 5 and 6.
而且，本發明該該理財分析模組(23)進一步進行一退休規劃演算(234)，係取得該臉部影像(11)的年齡資料(C1)、性別資料(C2)及情緒資料(C3)後，利用政府統計每人每月消費支出數據(如透過網路取得行政院主計處平均每人每月消費支出統計數據進行比對)，計算出退休後總花費，依蒙地卡羅(Monte Carlo)方法模擬1萬次市場投資情況，推算出最佳的投資金額，於退休時得到足夠的資產，以滿足退休後的花費。再者，該理財分析模組(23)進一步進行一保險計算演算(235)，係取得該臉部影像(11)的年齡資料(C1)、性別資料(C2)後，依不同性別、在不同年齡層所屬不同人生階段的需求數據，針對壽險、意外險、產險、醫療險與重大疾病險規劃保障內容；如市面壽險業者所使用的人生階段投保方法，以年齡劃分不同的四個階段 包含第一為小孩時期(15歲以下)、第二為青少年時期(15~25歲)、第三為壯年時期(25~50歲)、第四為老年時期(50歲以上)。依最適的保險費用比例計算出建議投保金額，並分配於規劃的保險中。另外，該理財分析模組(23)進一步進行一貸款計算演算(236)，係取得該臉部影像(11)的年齡資料(C1)後，利用政府統計各年齡層收入分佈數據(如透過網路取得行政院主計處按年齡分收入統計數據進行比對)，依預估財力計算出可貸款金額。 Moreover, the financial analysis module (23) of the present invention further performs a retirement planning calculation (234) to obtain age data (C1), gender data (C2) and emotion data (C3) of the facial image (11) Afterwards, using government statistics per capita monthly consumption expenditure data (such as obtaining statistics on average per capita monthly consumption expenditure from the Accounting Office of the Executive Yuan through the Internet for comparison) to calculate the total expenditure after retirement, according to Monte Carlo (Monte Carlo) The Carlo) method simulates 10,000 times of market investment, and calculates the best investment amount to get enough assets at retirement to meet the expenditure after retirement. Furthermore, the financial analysis module (23) further performs an insurance calculation calculation (235) to obtain the age data (C1) and gender data (C2) of the facial image (11), according to different genders and different genders. Demand data for different life stages of the age group, planning coverage for life insurance, accident insurance, property insurance, medical insurance, and critical illness insurance; such as the life stage insurance method used by life insurance companies in the market, which is divided into four different stages by age Including the first is the child period (under 15 years old), the second is the teenage period (15-25 years old), the third is the prime of life (25-50 years old), and the fourth is the old age (over 50 years old). Calculate the recommended insurance amount based on the most appropriate insurance cost ratio and allocate it to the planned insurance. In addition, the financial analysis module (23) further performs a loan calculation calculation (236), which is to obtain the age data (C1) of the facial image (11), and use government statistics on the income distribution data of each age group (such as online Lu obtained the statistical data of income by age from the Chief Accounting Office of the Executive Yuan for comparison), and calculated the loanable amount based on estimated financial resources.
最後，該影像輸入端(10)傳送的該臉部影像(11)為取自安裝有應用程式的手機/電腦所上傳的照片，使一般民眾也可透過上傳照片傳送至伺服器主機(20)，經由人臉辨識模組(22)辨識出年齡、性別及情緒心情，計算產出該理財規劃結果(D)，提供他們參考。 Finally, the face image (11) sent by the image input terminal (10) is a photo taken from a mobile phone/computer with an application installed, so that ordinary people can also upload photos to the server host (20) , Recognize age, gender and emotional mood through the face recognition module (22), calculate and produce the financial planning result (D), provide them for reference.
由上所述者僅為用以解釋本發明之較佳實施例，並非企圖據以對本發明做任何形式上之限制，是以，凡有在相同之創作精神下所做有關本發明之任何修飾或變更者，為其他可據以實施之型態且具有相同效果者，皆仍應包括在本發明意圖保護之範疇內。 The above are only used to explain the preferred embodiments of the present invention, and are not intended to limit the present invention in any form. Therefore, any modification related to the present invention made under the same creative spirit Or changes, other types that can be implemented and have the same effect, should still be included in the scope of the present invention.
(10)‧‧‧影像輸入端 (10)‧‧‧Video input terminal
(11)‧‧‧臉部影像 (11)‧‧‧Face image
(20)‧‧‧伺服器主機 (20)‧‧‧Server Host
(21)‧‧‧人臉特徵資料集 (21)‧‧‧Face feature dataset
(22)‧‧‧人臉辨識模組 (22)‧‧‧Face recognition module
(23)‧‧‧理財分析模組 (23)‧‧‧Financial Analysis Module
(30)‧‧‧顯示設備 (30)‧‧‧Display equipment
(40)‧‧‧路由器 (40)‧‧‧ Router
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