DocumentCode :
167374
Title :
Very low resolution face reconstruction based on multi-output regression
Author :
Zhihui Li ; Ying Hou ; Haibo Liu ; Xiang Li
Author_Institution :
Coll. of Comput. Sci. & Technol., Harbin Eng. Univ., Harbin, China
fYear :
2014
fDate :
8-9 May 2014
Firstpage :
74
Lastpage :
77
Abstract :
According to the reconstruction in the existing systems whose model is big and reconstruct speed is slow as the actual situation, this paper proposes a piece-division multiple output regression algorithm based on the Bayesian multiple adaptive regression splines ( MARS )model to make the regression of very low resolution(VLR) face data. This paper studies the low resolution(LR) face image reconstruction, which has less data, using the regression method to reconstruction is the most appropriate way with small model, fast reconstruction speed and accurate results as its advantages. The experiments prove the reconstruction accuracy from error and identification accuracy two aspects in this paper.
Keywords :
face recognition; image reconstruction; regression analysis; splines (mathematics); Bayesian multiple adaptive regression splines model; MARS model; piece-division multiple output regression algorithm; very low resolution face image reconstruction; Adaptation models; Artificial neural networks; Image restoration; Surveillance; Training; MARS; Multi-output regression; Super-resolution; face reconstruction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics, Computer and Applications, 2014 IEEE Workshop on
Conference_Location :
Ottawa, ON
Type :
conf
DOI :
10.1109/IWECA.2014.6845560
Filename :
6845560
Link To Document :
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