DocumentCode :
2400135
Title :
Where am I: Place instance and category recognition using spatial PACT
Author :
Wu, Jianixn ; Rehg, James M.
Author_Institution :
Sch. of Interactive Comput., Georgia Inst. of Technol., Atlanta, GA
fYear :
2008
fDate :
23-28 June 2008
Firstpage :
1
Lastpage :
8
Abstract :
We introduce spatial PACT (principal component analysis of census transform histograms), a new representation for recognizing instances and categories of places or scenes. Both place instance recognition (ldquoI am in Room 113rdquo) and category recognition (ldquoI am in an officerdquo) have been widely researched. Features that have different discriminative power/invariance tradeoff have been used separately for the two tasks. PACT captures local structures of an image through the census transform (CT), while large-scale structures are captured by the strong correlation between neighboring CT values and the histogram. The PCA operation ignores noise in the histogram distribution, computes important ldquoprimitive shapesrdquo, and results in a compact representation. Spatial PACT, a spatial pyramid of PACT, further incorporates global structures in the image. Our experiments demonstrate that spatial PACT outperforms the current state-of-the-art in several place and scene recognition, and shape matching datasets. Besides, spatial PACT is easy to implement. It has nearly no parameter to tune, and evaluates extremely fast.
Keywords :
image recognition; principal component analysis; transforms; category recognition; census transform histogram; place instance recognition; principal component analysis; spatial PACT; Cameras; Computed tomography; Histograms; Image recognition; Layout; Principal component analysis; Robot localization; Robot vision systems; Sensor phenomena and characterization; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on
Conference_Location :
Anchorage, AK
ISSN :
1063-6919
Print_ISBN :
978-1-4244-2242-5
Electronic_ISBN :
1063-6919
Type :
conf
DOI :
10.1109/CVPR.2008.4587627
Filename :
4587627
Link To Document :
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