Title
Saliency oriented object image re-ranking
Abstract
For image retrieval, most users hope to retrieve a certain salient object instead of an obscure pattern in an image. This paper presents a novel object re-ranking algorithm based on visual saliency, which is employed to detect salient object regions in an image. The re-ranking is carried out with a SVM classifier on the salient regions to assure that the images ranked on the top of the list exhibit salient object pictures. To speed up the classifier training, a small code book (1K) is chosen. To improve the re-ranking efficacy, we employ the posterior probability of the salient region to adjust re-ranking, and derive an approximate formula of the posterior probability of the salient region. The formula is based on a hierarchical model, containing spatial information to compensate the feature disorder of the model of bags of visual words (BoVW). The posterior probability is calculated offline, so the online efficiency of re-ranking is high. Experiments demonstrate that our algorithm significantly improves online efficiency and saliency while possesses high accuracy of image retrieval.
Year
DOI
Venue
2014
10.1109/ICECS.2014.7049999
ICECS
Keywords
Field
DocType
small code book,image re-ranking,visual saliency,salient object retrieval,spatial information,posterior probability,salient regions,svm classifier,reranking efficacy,classifier training,salient object,image classification,saliency oriented object image reranking,feature disorder compensation,image retrieval,small codebook,bags of visual words model,object reranking algorithm,salient object pictures,bovw model,support vector machines,hierarchical model,probability
Computer vision,Pattern recognition,Computer science,Salience (neuroscience),Support vector machine,Image retrieval,Posterior probability,Artificial intelligence,Contextual image classification,Statistical classification,Visual Word,Salient
Conference
Citations 
PageRank 
References 
0
0.34
7
Authors
3
Name
Order
Citations
PageRank
Chao Xu1132762.65
Yuan Gao200.68
Miaojing Shi318611.27