DocumentCode :
3088245
Title :
Depth estimation from monocular infrared images based on BP neural network model
Author :
Shaoyuan Sun ; Linna Li ; Lin Xi
Author_Institution :
Autom. Dept., Donghua Univ., Shanghai, China
fYear :
2012
fDate :
16-18 Dec. 2012
Firstpage :
237
Lastpage :
241
Abstract :
A depth estimation algorithm for monocular infrared image based on nonlinear learning model is proposed in this paper. Firstly, some infrared image features corresponding to the depth are extracted using stepwise regression and independent component analysis. Secondly, we regress and train the features and the corresponding depth map of an infrared image based on BP neural network. A nonlinear depth estimation model is obtained. We can estimate depth distribution of an infrared image using the model. The experimental results show that more accurate depth information can obtained based on the proposed model comparing the linear estimation model.
Keywords :
backpropagation; computer vision; feature extraction; independent component analysis; infrared imaging; neural nets; regression analysis; BP neural network model; depth distribution; independent component analysis; infrared image feature extraction; linear estimation model; monocular infrared Image; nonlinear depth estimation; nonlinear learning model; stepwise regression; Artificial neural networks; Automation; Educational institutions; BP neural network; depth estimation; infrared image; monocular depth;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision in Remote Sensing (CVRS), 2012 International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4673-1272-1
Type :
conf
DOI :
10.1109/CVRS.2012.6421267
Filename :
6421267
Link To Document :
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