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Intelligent Digital Signage System Based on Gender Identification

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Intelligent Embedded Systems

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 492))

Abstract

This paper proposes an intelligent transformation of digital signage systems by making it more audience interactive. The increase in flexibility and enhancement of digital signage display system can be done by providing optimized information and appearance attractive multimedia content through the signage system. This emphasizes more on the advertisement industry especially in public spaces like hotels, airports. The system has been designed to broadcast the advertisement on the signage display system based on the demographic features like gender of the observer. Real-time computer vision algorithms are applied to provide an observer-specific advertisement broadcast on the display system.

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References

  1. Ravnik R, Solina F (2013) Interactive and audience adaptive digital signage using real-time computer vision. Int J Adv Rob Sys. 10(2):107

    Article  Google Scholar 

  2. Alrashed HF, Berbar MA (2013) Facial gender recognition using eyes images. Int J Adv Res Comput Commun Eng. 2(6):2441–2445 June

    Google Scholar 

  3. Bera S (2014–2015) Gender recognition from facial images using support vector machine; Shirkey DM, Gupta SR (2013) An image mining system for gender classification & age prediction based on facial features. Int J Sci Mod Eng (IJISME) 1(6). ISSN:2319-6386

    Google Scholar 

  4. Basha AF, Jahangeer GSB (2014) Exploring a novel method for face image gender classification using random forest and comparing with other machine learning techniques. Int J Comput Sci Issues (IJCSI) 11(6):2

    Google Scholar 

  5. Zhang C-Y, Ruan Q-Q (2010) Face recognition using L-fisherfaces. J Inform Sci Eng 26:1525–1537

    Google Scholar 

  6. Ravi S, Wilson S (2010) Face detection with facial features and gender classification based on support vector machine. Int J Imaging Sci Eng 23–28

    Google Scholar 

  7. Singh V, Shokeen V, Singh B (2013) Comparison of feature extraction algorithms for gender classification from face images. Int J Eng Res Technol

    Google Scholar 

  8. Belhumeur PN, Hespanha J, Kriegman D (1997) Eigenfaces vs. fisherfaces: recognition using class specific linear projection. IEEE Trans Pattern Anal Mach Intell. 19(7):711–720

    Article  Google Scholar 

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Correspondence to Riya Elizabeth Abraham or M. Robert Kennedy .

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© 2018 Springer Nature Singapore Pte Ltd.

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Abraham, R.E., Robert Kennedy, M. (2018). Intelligent Digital Signage System Based on Gender Identification. In: Thalmann, D., Subhashini, N., Mohanaprasad, K., Murugan, M. (eds) Intelligent Embedded Systems. Lecture Notes in Electrical Engineering, vol 492. Springer, Singapore. https://doi.org/10.1007/978-981-10-8575-8_25

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  • DOI: https://doi.org/10.1007/978-981-10-8575-8_25

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8574-1

  • Online ISBN: 978-981-10-8575-8

  • eBook Packages: EngineeringEngineering (R0)

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