人數計算、性別年齡辨識與眼神注視偵測應用於櫥窗廣告系統之關注度估測;People Counting, Gender and Edge Recognition, and Eye Gaze Detection with Application to Interest Degree Estimation in Window Advertisement Systems

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Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/62940

Title:	人數計算、性別年齡辨識與眼神注視偵測應用於櫥窗廣告系統之關注度估測;People Counting, Gender and Edge Recognition, and Eye Gaze Detection with Application to Interest Degree Estimation in Window Advertisement Systems
Authors:	范國清
Contributors:	國立中央大學資訊工程系
Keywords:	資訊科學;軟體
Date:	2012-12-01
Issue Date:	2014-03-17 14:14:49 (UTC+8)
Publisher:	行政院國家科學委員會
Abstract:	研究期間：10108~10207;Under the circumstance of high economic development society, tremendous resources and human effort have to be spent to investigate one’s buying behavior in selling a product or preparing a show. The reasons why need such resources and efforts are twofolds. One is the inefficiency of investigation mechanism which is usually accomplished by analyzing questionares or custom’s records. Another is the lacking of matching hardwares which is usually done by manual statistic analysis and data collection. In response to these needs, a vision-based custom purchasing behavior investigation system is proposed. In our system, a camera is mounted directly above the advertising merchandises to capture custom’s video sequence passing by. Through image analysis and pattern recognition, we can recognize the gender and age of consumers on which significant statistic data, such as the number of people staring at the merchandises, can be obtained.We plan to develop the system in three years. In the first year, we plan to accomplish two tasks including people counting and frontal face detection such that we can count the number of passengers who has interest to the merchandises. In the second year, we plan to analyze the walking behavior to recognize the gender and age of the passengers. In the meantime, the frontal faces of passengers who have interest in the merchandises will be captured. We will also analyze the frontal faces of passengers to confirm their gender and age. In the third year, three types of features will be analyzed to estimate the interest degree of the passengers who has interest to the merchandises. These three types of features include walking behavior, the period of eye staring, and facial expression. The whole system will be integrated in the third year also.
Relation:	財團法人國家實驗研究院科技政策研究與資訊中心
Appears in Collections:	[Department of Computer Science and information Engineering] Research Project

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