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논문 기본 정보

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학술저널
저자정보
Lee, Dongwoo (NAMUGA Co., Ltd.) Kim, Daehyun (NAMUGA Co., Ltd.) Lee, Junghoon (Dept. of Electrical Information Control, Dongseoul College) Lee, Seungyoun (Dept. of Electrical Information Control, Dongseoul College) Hwang, Hyunsuk (Dept. of Electrical Engineering, Seoil University) Mariappan, Vinayagam (Graduate School of Nano IT Design Fusion, Seoul National Univ. of Science & Tech.) Lee, Minwoo (Graduate School of Nano IT Design Fusion, Seoul National Univ. of Science & Tech.) Cha, Jaesang (Graduate School of Nano IT Design Fusion, Seoul National Univ. of Science & Tech.)
저널정보
(사)국제문화기술진흥원 The International journal of advanced culture technology The International journal of advanced culture technology 제5권 제1호
발행연도
2017.1
수록면
51 - 57 (7page)

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Digital signage is becoming part of daily life across a wide range of visual advertisements segments market used in stations, hotels, retail stores, hotels, etc. The current digital signage system used in market is generally works on limited user interactivity with static contents. In this paper, a new approach is proposed using computer vision based dynamic audience adaptive cost-effective digital signage system. The proposed design uses the Camera attached Raspberry Pi Open source platform to employ the real-time audience interaction using computer vision algorithms to extract facial features of the audience. The real-time facial features are extracted using Haar Cascade algorithm which are used for audience gender specific rendering of dynamic digital signage content. The audience facial characterization using Haar Cascade is evaluated on the FERET database with 95% accuracy for gender classification. The proposed system, developed and evaluated with male and female audiences in real-life environments camera embedded raspberry pi with good level of accuracy.

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