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Robust Face Tracking Using Siamese-VGG with Pre-training and Fine-tuning

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成果类型:
会议论文
作者:
Yuan, Shuo*;Yu, Xinguo;Majid, Abdul
通讯作者:
Yuan, Shuo
作者机构:
[Yuan, Shuo; Yu, Xinguo] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.
[Majid, Abdul] Wollongong Joint Inst Cent China Normal Univ, Wuhan, Hubei, Peoples R China.
通讯机构:
[Yuan, Shuo] C
Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China.
语种:
英文
关键词:
Siamese Net;VGG;face tracking;convolutional neural network;L2 regularization
期刊:
2019 4TH INTERNATIONAL CONFERENCE ON CONTROL AND ROBOTICS ENGINEERING (ICCRE)
年:
2019
页码:
170-174
会议名称:
2019 4th International Conference on Control and Robotics Engineering (ICCRE)
机构署名:
本校为第一且通讯机构
院系归属:
国家数字化学习工程技术研究中心
摘要:
In order to analyze facial expression in human-computer interaction, real time face-tracking has become significant research problem. Traditional face tracking methods have achieved good results in some constrained environments (such as good illumination, no background interference, etc.) However,these methods require to design manual facial features depending on researcher's experience. In addition,lacking ability for generalization problems is worthy of study. The robustness of face tracking in complex scenes is challenging due to fast moving, multi-scale changes, rotation and occlusion, ill...

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