A novel semi-supervised face recognition for video
作者： Ke Lu , Zhengming Ding , Jidong Zhao , Yue Wu
DOI: 10.1109/ICICIP.2010.5564344
关键词:
摘要: Video-based face recognition has been one of the hot topics in field pattern last few decades. In this paper, incorporating Support Vector Machines (SVM) and Locality Preserving Projections (LPP), we propose a novel semi-supervised algorithm for video, which can discover more space-time semantic information hidden video sequence, simultaneously make full use small amount labeled data with plentiful unknown intrinsic nonlinear structure to extract discriminative manifold features. We also compare our other algorithms on UCSD/Honda Video Database. The experimental results show that proposed outperform state-of-the-art solutions videobased recognition.
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