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Información general |
| Autor |
Ravnik, Robert; Solina, Franc |
| Publicado |
InTech Open Access Publisher, 2013
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| Abstract |
In this paper we present the development of an
interactive, content‐aware and cost‐effective digital signage
system. Using a monocular camera installed within the
frame of a digital signage display, we employ real‐time
computer vision algorithms to extract temporal, spatial and
demographic features of the observers, which are further
used for observer‐specific broadcasting of digital signage
content. The number of observers is obtained by the Viola
and Jones face detection algorithm, whilst facial images are
registered using multi‐view Active Appearance Models.
The distance of the observers from the system is estimated
from the interpupillary distance of registered faces.
Demographic features, including gender and age group,
are determined using SVM classifiers to achieve individual
observer‐specific selection and adaption of the digital
signage broadcasting content. The developed system was
evaluated at the laboratory study level and in a field study
performed for audience measurement research.
Comparison of our monocular localization module with
the Kinect stereo‐system reveals a comparable level of
accuracy. The facial characterization module is evaluated
on the FERET database with 95% accuracy for gender
classification and 92% for age group. Finally, the field
study demonstrates the applicability of the developed
system in real‐life environments. |
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International Journal of Advanced Robotic Systems
Autor: Ottaviano, Erika; Ceccarelli, Marco; Husty, Manfred; Yu, Sung-Hoon; Kim, Yong-Tae; Park, Chang-Woo; Hyun, Chang-Ho; Chen, Xiulong; Feng, Weiming; Sun, Xianyang; Gao, Qing; Grigorescu, Sorin M.; Pozna, Claudiu; Liu, Wanli; Zhankui, Wang; Guo, Meng; Fu, Guoyu; Zhang, Jin; Chen, Wenyuan; Peng, Fengchao; Yang, Pei; Chen, Chunlin; Ding, Rui; Yu, Junzhi; Yang, Qinghai; Tan, Min; Polden, Joseph; Pan, [...]
Publicado: 2004
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