Browsing by Subject "Indexing"

Now showing 1 - 5 of 5

Open Access
Automatic detection of salient objects and spatial relations in videos for a video database system
(Elsevier BV, 2008-10) Sevilmiş, T.; Baştan M.; Güdükbay, Uğur; Ulusoy, Özgür
Multimedia databases have gained popularity due to rapidly growing quantities of multimedia data and the need to perform efficient indexing, retrieval and analysis of this data. One downside of multimedia databases is the necessity to process the data for feature extraction and labeling prior to storage and querying. Huge amount of data makes it impossible to complete this task manually. We propose a tool for the automatic detection and tracking of salient objects, and derivation of spatio-temporal relations between them in video. Our system aims to reduce the work for manual selection and labeling of objects significantly by detecting and tracking the salient objects, and hence, requiring to enter the label for each object only once within each shot instead of specifying the labels for each object in every frame they appear. This is also required as a first step in a fully-automatic video database management system in which the labeling should also be done automatically. The proposed framework covers a scalable architecture for video processing and stages of shot boundary detection, salient object detection and tracking, and knowledge-base construction for effective spatio-temporal object querying. © 2008 Elsevier B.V. All rights reserved.
Open Access
Matching ottoman words: an image retrieval approach to historical document indexing
(ACM, 2007-07) Ataer, Esra; Duygulu, Pınar
Large archives of Ottoman documents are challenging to many historians all over the world. However, these archives remain inaccessible since manual transcription of such a huge volume is difficult. Automatic transcription is required, but due to the characteristics of Ottoman documents, character recognition based systems may not yield satisfactory results. It is also desirable to store the documents in image form since the documents may contain important drawings, especially the signatures. Due to these reasons, in this study we treat the problem as an image retrieval problem with the view that Ottoman words are images, and we propose a solution based on image matching techniques. The bag-of-visterms approach, which is shown to be successful to classify objects and scenes, is adapted for matching word images. Each word image is represented by a set of visual terms which are obtained by vector quantization of SIFT descriptors extracted from salient points. Similar words are then matched based on the similarity of the distributions of the visual terms. The experiments are carried out on printed and handwritten documents which included over 10,000 words. The results show that, the proposed system is able to retrieve words with high accuracies, and capture the semantic similarities between words. Copyright 2007 ACM.
Open Access
Research issues in peer-to-peer data management
(IEEE, 2007-11) Ulusoy, Özgür
Data management in Peer-to-Peer (P2P) systems is a complicated and challenging issue due to the scale of the network and highly transient population of peers. In this paper, we identify important research problems in P2P data management, and describe briefly some methods that have appeared in the literature addressing those problems. We also discuss some open research issues and directions regarding data management in P2P systems. ©2007 IEEE.
Open Access
Segmentation-based extraction of important objects from video for object-based indexing
(IEEE, 2008-06) Baştan, Muhammet; Güdükbay, Uğur; Ulusoy, Özgür
We describe a method to automatically extract important video objects for object-based indexing. Most of the existing salient object detection approaches detect visually conspicuous structures in images, while our method aims to find regions that may be important for indexing in a video database system. Our method works on a shot basis. We first segment each frame to obtain homogeneous regions in terms of color and texture. Then, we extract a set of regional and inter-regional color, shape, texture and motion features for all regions, which are classified as being important or not using SVMs trained on a few hundreds of example regions. Finally, each important region is tracked within each shot for trajectory generation and consistency check. Experimental results from news video sequences show that the proposed approach is effective. © 2008 IEEE.
Open Access
Whole genome alignment via Alternating Lyndon Factorization Tree traversal
(2023-07) Aydın, Mahmud Sami
The Whole Genome Alignment Problem (WGA) is an important challenge in the field of genomics, especially in the context of pangenome construction. Here we propose a novel indexing structure called the Alternating Lyndon Factor-ization Tree (ALFTree), which incorporates both spatial and lexicographical information within its nodes. The ALFTree is a powerful tool for WGA, as it can efficiently store and retrieve information about large DNA sequences. We present an algorithm, namely Idoneous, specifically designed to construct the ALFTree from a given DNA sequence. The algorithm works by generating intervals of specific sizes, identifying matches within these intervals, and perform-ing a sanity check through alignment procedures. The algorithm is efficient and scalable, making it a valuable tool for WGA. Some of the key features of the ALFTree are 1) compact and efficient data structure for storing large DNA sequences; 2) efficient retrieval of information about specific regions of a DNA sequence; 3) ability to handle both spatial and lexicographical information; and 4) scalability to large DNA sequences. Our experimental results on different genomes highlight the effects of param-eter selections on coverage and identity. Idoneous demonstrates competitive per-formance in terms of coverage and provides flexibility in adjusting sensitivity and specificity for different alignment scenarios. The ALFTree has the potential to significantly improve the performance of WGA algorithms. We believe that the ALFTree is a valuable contribution to the field of genomics, and we hope that it will be used by researchers to accelerate the pace of discovery.