DocumentCode :
3518025
Title :
Interesting region detection in aerial video using Bayesian topic models
Author :
Wang, Jiewei ; Wang, Yunhong ; Zhang, Zhaoxiang
Author_Institution :
Lab. of Intell. Recognition & Image Process., Beihang Univ., Beijing, China
fYear :
2011
fDate :
28-28 Nov. 2011
Firstpage :
706
Lastpage :
710
Abstract :
Searching interesting regions in aerial video is a new and challenging problem. This paper presents an approach to detect visual interesting regions in aerial video using pLSA topic model. Traditional interesting region detection approaches just use bottom-up information, such as color, orientation and movement etc. Our proposed method can discover the semantic content of the whole image, the co-occurrence of local image patches via pLSA model, and consequently improve detection result significantly in real world scenes. First, we extract frames from aerial video as documents. Then we use vector quantized SIFT descriptors as words. Third, we discover topics (e.g. plants, roads, buildings) and the relation among them using pLSA model. Finally, we can detect interesting regions as we need according to calculated models. Experimental observations show the success of our approach on interesting region detection in aerial video.
Keywords :
Bayes methods; object detection; vector quantisation; video signal processing; Bayesian topic models; aerial video; bottom-up information; frame extraction; image semantic content discovery; local image patches; pLSA topic model; probabilistic latent semantic analysis; real world scenes; topics discovery; vector quantized SIFT descriptors; visual interesting region detection; Detectors; Histograms; Observers; Semantics; Vectors; Visualization; Vocabulary;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ACPR), 2011 First Asian Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4577-0122-1
Type :
conf
DOI :
10.1109/ACPR.2011.6166550
Filename :
6166550
Link To Document :
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