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General information |
| Author |
Yeom, Seokwon; Woo, Yong-Hyun |
| Published |
InTech Open Access Publisher, 2013
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| Abstract |
Face detection and recognition have wide
applications in robot vision and intelligent surveillance.
However, face identification at a distance is very
challenging because long‐distance images are often
degraded by low resolution, blurring and noise. This
paper introduces a person‐specific face detection method
that uses a nonlinear optimum composite filter and
subsequent verification stages. The filter’s optimum
criterion minimizes the sum of the output energy
generated by the input noise and the input image. The
composite filter is trained with several training images
under long‐distance modelling. The candidate facial
regions are provided by the filter’s outputs of the input
scene. False alarms are eliminated by subsequent testing
stages, which comprise skin colour and edge mask
filtering tests. In the experiments, images captured by a
webcam and a CCTV camera are processed to show the
effectiveness of the person‐specific face detection system
at a long distance. |
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International Journal of Advanced Robotic Systems
Author: 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, [...]
Published: 2004
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