A Distributed M-Tree for Similarity Search in Large Multimedia Database on Spark

2020 ◽  
pp. 146-164
Author(s):  
Phuc Do ◽  
Trung Hong Phan
Keyword(s):  
Range Query ◽  
Multimedia Databases ◽  
Tree Structure ◽  
Index Structure ◽  
Multimedia Database ◽  
Range Queries ◽  
Complex Objects ◽  
Video Clips ◽  
Knn Query ◽  
Spark Framework

In this chapter, Image2vec or Video2vector are used to convert images and video clips to vectors in large multimedia database. The M-tree is an index structure that can be used for the efficient resolution of similarity queries on complex objects. M-tree can be profitably used for content-based retrieval on multimedia databases provided relevant features have been extracted from the objects. In a large multimedia database, to search for similarities such as k-NN queries and Range queries, distances from the query object to all remaining objects (images or video clips) are calculated. The calculation between query and entities in a large multimedia database is not feasible. This chapter proposes a solution to distribute the M-Tree structure on the Apache Spark framework to solve the Range Query and kNN Query problems in large multimedia database with a lot of images and video clips.

scholarly journals Efficient Historical Query in HBase for Spatio-Temporal Decision Support

2016 ◽  
Vol 11 (5) ◽  
pp. 613 ◽  
Author(s):  
Xiaoying Chen ◽  
Chong Zhang ◽  
Bin Ge ◽  
Weidong Xiao
Keyword(s):  
Decision Support ◽  
Storage System ◽  
Range Query ◽  
Index Structure ◽  
Temporal Data ◽  
Effective Solution ◽  
Nosql Database ◽  
Knn Query ◽  
Spatio Temporal ◽  
Analysis Platform

Comparing to last decade, technologies to gather spatio-temporal data are more and more developed and easy to use or deploy, thus tens of billions, even trillions of sensed data are accumulated, which poses a challenge to spatio-temporal Decision Support System (stDSS). Traditional database hardly supports such huge volume, and tends to bring performance bottleneck to the analysis platform. Hence in this paper, we argue to use NoSQL database, HBase, to replace traditional back-end storage system. Under such context, the well-studied spatio-temporal querying techniques in traditional database should be shifted to HBase system parallel. However, this problem is not solved well in HBase, as many previous works tackle the problem only by designing schema, i.e., designing row key and column key formation for HBase, which we don’t believe is an effective solution. In this paper, we address this problem from nature level of HBase, and propose an index structure as a built-in component for HBase. STEHIX (Spatio-TEmporal Hbase IndeX) is adapted to two-level architecture of HBase and suitable for HBase to process spatio-temporal queries. It is composed of index in the meta table (the first level) and region index (the second level) for indexing inner structure of HBase regions. Base on this structure, three queries, range query, kNN query and GNN query are solved by proposing algorithms, respectively. For achieving load balancing and scalable kNN query, two optimizations are also presented. We implement STEHIX and conduct experiments on real dataset, and the results show our design outperforms a previous work in many aspects.

Multimedia Databases and Data Management

2012 ◽  
pp. 1-11
Author(s):  
Shu-Ching Chen
Keyword(s):  
Data Management ◽  
Relevant Information ◽  
Multimedia Databases ◽  
Multimedia Data ◽  
Formal Structure ◽  
Multimedia Database ◽  
Storage Devices ◽  
Temporal Relationships ◽  
Spatio Temporal ◽  
Application Requirements

The exponential growth of the technological advancements has resulted in high-resolution devices, such as digital cameras, scanners, monitors, and printers, which enable the capturing and displaying of multimedia data in high-density storage devices. Furthermore, more and more applications need to live with multimedia data. However, the gap between the characteristics of various media types and the application requirements has created the need to develop advanced techniques for multimedia data management and the extraction of relevant information from multimedia databases. Though many research efforts have been devoted to the areas of multimedia databases and data management, it is still far from maturity. The purpose of this article is to discuss how the existing techniques, methodologies, and tools addressed relevant issues and challenges to enable a better understanding in multimedia databases and data management. The focuses include: (1) how to develop a formal structure that can be used to capture the distinguishing content of the media data in a multimedia database (MMDB) and to form an abstract space for the data to be queried; (2) how to develop advanced content analysis and retrieval techniques that can be used to bridge the gaps between the semantic meaning and low-level media characteristics to improve multimedia information retrieval; and (3) how to develop query mechanisms that can handle complex spatial, temporal, and/or spatio-temporal relationships of multimedia data to answer the imprecise and incomplete queries issued to an MMDB.

A NOVEL INDEXING AND ACCESS MECHANISM USING AFFINITY HYBRID TREE FOR CONTENT-BASED IMAGE RETRIEVAL IN MULTIMEDIA DATABASES

2007 ◽  
Vol 01 (02) ◽  
pp. 147-170 ◽  
Author(s):  
KASTURI CHATTERJEE ◽  
SHU-CHING CHEN
Keyword(s):  
Image Retrieval ◽  
Metric Spaces ◽  
Nearest Neighbor ◽  
Human Perception ◽  
Multimedia Databases ◽  
Multimedia Retrieval ◽  
Index Structure ◽  
Content Based Image Retrieval ◽  
K Nearest Neighbor ◽  
Computational Overhead

An efficient access and indexing framework, called Affinity Hybrid Tree (AH-Tree), is proposed which combines feature and metric spaces in a novel way. The proposed framework helps to organize large image databases and support popular multimedia retrieval mechanisms like Content-Based Image Retrieval (CBIR). It is efficient in terms of computational overhead and fairly accurate in producing query results close to human perception. AH-Tree, by being able to introduce the high level semantic image relationship as it is in its index structure, solves the problem of translating the content-similarity measurement into feature level equivalence which is both painstaking and error-prone. Algorithms for similarity (range and k-nearest neighbor) queries are implemented and extensive experiments are performed which produces encouraging results with low I/O and distance computations and high precision of query results.

scholarly journals Optimizing Range Query Processing for Dual Bitmap Index

2018 ◽  
Vol 16 (2) ◽  
pp. 133-142
Author(s):  
Naphat KEAWPIBAL ◽  
Ladda PREECHAVEERAKUL ◽  
Sirirut VANICHAYOBON
Keyword(s):  
Query Processing ◽  
Range Query ◽  
Range Queries ◽  
Boolean Operations ◽  
Bitmap Index ◽  
Indexing Method ◽  
Overall Performance ◽  
Optimizing Algorithm ◽  
Bitmap Indexes ◽  
Range Query Processing

Bitmap-based indexes are known to be the most effective indexing method for retrieving and answering selective queries in a read-only environment. Various types of encoding bitmap indexes significantly improve query time efficiency by utilizing fast Boolean operations directly on the index before retrieving the raw data. In particular, the dual bitmap index improves the performance of equality queries in terms of the space vs. time trade-off. However, the performance of range queries is unsatisfactory. In this paper, an optimizing algorithm is proposed to improve the range query processing for the dual bitmap index. The results of the experiment conducted show that the proposed algorithm, called Dual-simRQ, reduces the number of bitmap vectors scanned and the Boolean operations performed, which impacts the overall performance for range query processing.

A multimedia bilingual database for the lexicon of Swiss German Sign Language

2001 ◽  
Vol 4 (1-2) ◽  
pp. 133-143 ◽  
Author(s):  
Penny Boyes-Braem
Keyword(s):  
German Text ◽  
Sign Language ◽  
Large Scale ◽  
Multimedia Database ◽  
Line Drawings ◽  
Swiss German ◽  
Video Clips ◽  
Linguistic Research ◽  
Base Form ◽  
German Sign Language

This multimedia database project is the first large-scale collection and description of the signs of Swiss German Sign Language (Deutschschweizerische Gebärdensprache, DSGS). The aim of the database is to gather linguistic information on the DSGS lexicon which can serve as a basis for future dictionaries and teaching materials, as well as function as a tool for linguistic research. For each lexical entry, there is information about all of the sign’s meanings, its morphological and syntactic characteristic, several categories of usage (geographical and generation variation, style, register) as well as example links to videotaped signed sentences. The information about each lexical item is represented in the database in several different forms: Video clips of the base form of the sign and of signed sentences in which it appears, line drawings, information checkboxes, form notation (HamNoSys and SignWriting), as well as German text.

Multimedia Databases and Data Management

2010 ◽  
Vol 1 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Shu-Ching Chen
Keyword(s):  
Data Management ◽  
Relevant Information ◽  
Multimedia Databases ◽  
Multimedia Data ◽  
Formal Structure ◽  
Multimedia Database ◽  
Storage Devices ◽  
The Media ◽  
Spatio Temporal ◽  
Application Requirements

The exponential growth of the technological advancements has resulted in high-resolution devices, such as digital cameras, scanners, monitors, and printers, which enable the capturing and displaying of multimedia data in high-density storage devices. Furthermore, more and more applications need to live with multimedia data. However, the gap between the characteristics of various media types and the application requirements has created the need to develop advanced techniques for multimedia data management and the extraction of relevant information from multimedia databases. Though many research efforts have been devoted to the areas of multimedia databases and data management, it is still far from maturity. The purpose of this article is to discuss how the existing techniques, methodologies, and tools addressed relevant issues and challenges to enable a better understanding in multimedia databases and data management. The focuses include: (1) how to develop a formal structure that can be used to capture the distinguishing content of the media data in a multimedia database (MMDB) and to form an abstract space for the data to be queried; (2) how to develop advanced content analysis and retrieval techniques that can be used to bridge the gaps between the semantic meaning and low-level media characteristics to improve multimedia information retrieval; and (3) how to develop query mechanisms that can handle complex spatial, temporal, and/or spatio-temporal relationships of multimedia data to answer the imprecise and incomplete queries issued to an MMDB.

Distributed Multimedia Databases

2002 ◽  
pp. 2-12 ◽  
Author(s):  
Timothy K. Shih
Keyword(s):  
Distributed Control ◽  
Digital Libraries ◽  
Database Systems ◽  
Video On Demand ◽  
Multimedia Databases ◽  
Multimedia Database ◽  
Network Technology ◽  
Distributed Multimedia ◽  
Multimedia Computing ◽  
Systems Requirements

Distributed Multimedia Database involves network technology, distributed control, security, and multimedia computing. This chapter discusses fundamental concepts and introduces issues of image database and digital libraries, video-on-demand systems, multimedia synchronization, as well as some case studies of distributed multimedia database systems. Requirements of multimedia database management systems and their functions are also presented.

Normal Forms for Multimedia Databases

2013 ◽  
pp. 136-153
Author(s):  
Shi Kuo Chang ◽  
Vincenzo Deufemia ◽  
Giuseppe Polese
Keyword(s):  
Normal Forms ◽  
Similarity Measures ◽  
Multimedia Databases ◽  
Multimedia Data ◽  
Multimedia Database ◽  
Complex Data ◽  
Data Types ◽  
Semantic Relationships ◽  
Domain Specific ◽  
Different Types

In this chapter we present normal forms for the design of multimedia database schemes with reduced manipulation anomalies. To this aim we first discuss how to describe the semantics of multimedia attributes based upon the concept of generalized icons, already used in the modeling of multimedia languages. Then, we introduce new extended dependencies involving different types of multimedia data. Such dependencies are based on domain specific similarity measures that are used to detect semantic relationships between complex data types. Based upon these new dependencies, we have defined five normal forms for multimedia databases, some focusing on the level of segmentation of multimedia attributes, others on the level of fragmentation of tables.

A multimedia bilingual database for the lexicon of Swiss German Sign Language

2001 ◽  
Vol 4 (1-2) ◽  
pp. 133-143 ◽  
Author(s):  
Penny Boyes-Braem
Keyword(s):  
German Text ◽  
Sign Language ◽  
Large Scale ◽  
Multimedia Database ◽  
Line Drawings ◽  
Swiss German ◽  
Video Clips ◽  
Linguistic Research ◽  
Base Form ◽  
German Sign Language

This multimedia database project is the first large-scale collection and description of the signs of Swiss German Sign Language (Deutschschweizerische Gebärdensprache, DSGS). The aim of the database is to gather linguistic information on the DSGS lexicon which can serve as a basis for future dictionaries and teaching materials, as well as function as a tool for linguistic research. For each lexical entry, there is information about all of the sign’s meanings, its morphological and syntactic characteristic, several categories of usage (geographical and generation variation, style, register) as well as example links to videotaped signed sentences. The information about each lexical item is represented in the database in several different forms: Video clips of the base form of the sign and of signed sentences in which it appears, line drawings, information checkboxes, form notation (HamNoSys and SignWriting), as well as German text.

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