DocumentCode
2913355
Title
Partial similarity based nonparametric scene parsing in certain environment
Author
Zhang, Honghui ; Fang, Tian ; Che, Xiaowu ; Qinping Zhao ; Quan, Long
Author_Institution
Hong Kong Univ. of Sci. & Technol., Hong Kong, China
fYear
2011
fDate
20-25 June 2011
Firstpage
2241
Lastpage
2248
Abstract
In this paper we propose a novel nonparametric image parsing method for the image parsing problem in certain environment. A novel and efficient nearest neighbor matching scheme, the ANN bilateral matching scheme, is proposed. Based on the proposed matching scheme, we first retrieve some partially similar images for each given test image from the training image database. The test image can be well explained by these retrieved images, with similar regions existing in the retrieved images for each region in the test image. Then, we match the test image to the retrieved training images with the ANN bilateral matching scheme, and parse the test image by integrating multiple cues in a markov random field. Experiment on three datasets shows our method achieved promising parsing accuracy and outperformed two state-of-the-art nonparametric image parsing methods.
Keywords
image matching; image retrieval; image segmentation; neural nets; visual databases; ANN bilateral matching scheme; Markov random field; image retrieval; nearest neighbor matching scheme; novel nonparametric image parsing method; partial similarity based nonparametric scene parsing; training image database; Accuracy; Artificial neural networks; Convergence; Databases; Markov processes; Measurement; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on
Conference_Location
Providence, RI
ISSN
1063-6919
Print_ISBN
978-1-4577-0394-2
Type
conf
DOI
10.1109/CVPR.2011.5995348
Filename
5995348
Link To Document