出版社：National Defense University Barbaros Naval Sciences and Engineering Institute Journal of Naval Science and Engineering
摘要：In this paper we propose a novel approach of image representation for weakly supervised scene classification that mainly combine two popular methods in the literature: Bag-of-Words (BoW) modeling and probabilistic Latent Semantic Analysis (pLSA) modeling.The new image representation scheme called Cascaded pLSA performs pLSA in a hierarchical sense after the BoW representation based on SIFT features is extracted.We associate location information with the conventional BoW/pLSA algorithm by subdividing each image into sub-regions iteratively at different resolution levels and implementing a pLSA model for each sub-region individually.Finally,an image is represented by concatenated topic distributions of each sub-region.The performance of our method is compared with the most successful methods in the literature using the same dataset.In the experiments,it has been seen that the proposed method outperforms the others in that particular dataset.
其他摘要：Bu makalede imgelerin analiz edilmesi ve neticesinde içerik bilgilerine göre imgelerin taşıdıkları anlamlara uygun olarak sınıflandırılmaları hedeflenmiştir.Bu kapsamda zayıf denetimle sahne sınıflandırması sağlayan ve literatürde son zamanlarda sıkça baş
关键词：Scene Classification;Spatial Pyramid;probabilistic Latent Semantic Analysis;Bag-of-Visual words
其他关键词：Sahne Sınıflandırılması;Uzaysal Piramit;Olasılıksal Gizli Anlam Analizi;Görsel Kelimeler Kümesi
