Abstract

Estimation of demographic information from video sequence with people is a topic of growing interest in the last years. Indeed automatic estimation of audience statistics in digital signage as well as the human interaction in social robotic environment needs of increasingly robust algorithm for gender, race and age classification. In the present paper some of the state of the art features descriptors and sub space reduction approaches for gender, race and age group classification in video/image input are analyzed. Moreover a wide discussion about the influence of dataset distribution, balancing and cardinality is shown. The aim of our work is to investigate the best solution for each classification problem both in terms of estimation approach and dataset training. Additionally the computational problem it considered and discussed in order to contextualize the topic in a practical environment.

Autore Pugliese

• Carcagni' Pierluigi , Mazzeo Pier Luigi

Tutti gli autori

• Carcagnì P.; Del Coco M.; Mazzeo P.L.; Testa A.; Distante C.

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2014

ISSN

Non Disponibile

ISBN

9783319128108

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

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Numero di citazioni Scopus

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Ultimo Aggiornamento Citazioni

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Settori ERC

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Codici ASJC

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