An effective real time gender recognition system for smart cameras

Abstract

In recent years we have assisted to a growing interest for embedded vision, due to the availability of low cost hardware systems, effective for energy consumption, flexible for their size at the cost of limited (compared to the server) computing resources. Their use is boosted by the simplicity of their positioning in places where energy or network bandwidth is limited. Smart cameras are digital cameras embedding computer systems able to host video applications; due to the cost and the performance, they are progressively gaining popularity and conquering large amount of the market. Smart cameras are now able to host on board video applications, even if this imposes an heavy reformulation of the algorithms and of the software design so as to make them compliant with the limited CPUs and the small RAM and flash memory (typically of a few megabytes). In this paper we propose a method for gender recognition on video sequences, specifically designed for making it suited to smart cameras; although the algorithm uses very limited resources (in terms of RAM and CPU), it is able to run on smart cameras available today, presenting at the same time an high accuracy on unrestricted videos taken in real environments (malls, shops, etc.).

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Acknowledgements

This research has been partially supported by A.I. Tech s.r.l. (www.aitech.vision).

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Correspondence to Alessia Saggese.

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Carletti, V., Greco, A., Saggese, A. et al. An effective real time gender recognition system for smart cameras. J Ambient Intell Human Comput 11, 2407–2419 (2020). https://doi.org/10.1007/s12652-019-01267-5

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Keywords

  • Smart camera
  • Gender recognition
  • Gender recognition from video
  • Real-time
  • Face analysis
  • Video
  • Embedded vision