Browsing by Subject "Retrieval"

Now showing 1 - 2 of 2

Open Access
Cross-document word matching for segmentation and retrieval of Ottoman divans
(Springer U K, 2016) Duygulu, P.; Arifoglu, D.; Kalpakli, M.
Motivated by the need for the automatic indexing and analysis of huge number of documents in Ottoman divan poetry, and for discovering new knowledge to preserve and make alive this heritage, in this study we propose a novel method for segmenting and retrieving words in Ottoman divans. Documents in Ottoman are difficult to segment into words without a prior knowledge of the word. In this study, using the idea that divans have multiple copies (versions) by different writers in different writing styles, and word segmentation in some of those versions may be relatively easier to achieve than in other versions, segmentation of the versions (which are difficult, if not impossible, with traditional techniques) is performed using information carried from the simpler version. One version of a document is used as the source dataset and the other version of the same document is used as the target dataset. Words in the source dataset are automatically extracted and used as queries to be spotted in the target dataset for detecting word boundaries. We present the idea of cross-document word matching for a novel task of segmenting historical documents into words. We propose a matching scheme based on possible combinations of sequence of sub-words. We improve the performance of simple features through considering the words in a context. The method is applied on two versions of Layla and Majnun divan by Fuzuli. The results show that, the proposed word-matching-based segmentation method is promising in finding the word boundaries and in retrieving the words across documents. © 2014, Springer-Verlag London.
Open Access
Improved image-based localization using sfm and modified coordinate system transfer
(Institute of Electrical and Electronics Engineers, 2018) Salarian, M.; Iliev, N.; Çetin, A. Enis; Ansari, R.
Accurate localization of mobile devices based on camera-acquired visual media information usually requires a search over a very large GPS-referenced image database collected from social sharing websites like Flickr or services such as Google Street View. This paper proposes a new method for reliable estimation of the actual query camera location by optimally utilizing structure from motion (SFM) for three-dimensional (3-D) camera position reconstruction, and introducing a new approach for applying a linear transformation between two different 3-D Cartesian coordinate systems. Since the success of SFM hinges on effectively selecting among the multiple retrieved images, we propose an optimization framework to do this using the criterion of the highest intraclass similarity among images returned from retrieval pipeline to increase SFM convergence rate. The selected images along with the query are then used to reconstruct a 3-D scene and find the relative camera positions by employing SFM. In the last processing step, an effective camera coordinate transformation algorithm is introduced to estimate the query's geo-tag. The influence of the number of images involved in SFM on the ultimate position error is investigated by examining the use of three and four dataset images with different solution for calculating the query world coordinates. We have evaluated our proposed method on query images with known accurate ground truth. Experimental results are presented to demonstrate that our method outperforms other reported methods in terms of average error.