GeM-Tree: Towards a Generalized Multidimensional Index Structure Supporting Image and Video Retrieval

Chatterjee, Kasturi; Chen, Shu‐Ching

doi:10.1109/ism.2008.96

Cited by 9 publications

(16 citation statements)

References 11 publications

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“…We proposed several multimedia index structure for different multimedia data types including images, and videos in our previous works [4][5] [6]. [4] discusses a multidimensional index structure designed to handle images.…”

Section: Replicated Multidimensional Index Structurementioning

confidence: 99%

“…It can handle the hierarchical relationship among the different video units and facilitate intra and inter-unit retrieval strategies. Since having separate index structures for different multimedia data types can cause difficulty while embedding the index structure into the database kernel (both technical issues as well as optimization policy issues for other components residing in the kernel), [6] lays down a generalized index structure for managing both images and videos from one common platform. Additionally, it has the capability to be extended to support other forms of multimedia data such as documents.…”

Section: Replicated Multidimensional Index Structurementioning

confidence: 99%

“…Additionally, it has the capability to be extended to support other forms of multimedia data such as documents. [4][5] and [6] support the popular multimedia data retrieval strategy based on content without violating the underlying indexed space. Basically, the k-NN algorithm, which is the standard similarity search algorithm for tree-based indexes, is customized to support the content-based retrievals while considering the high-level semantic relationships among the data objects.…”

Section: Replicated Multidimensional Index Structurementioning

confidence: 99%

“…We chose AH-Tree as we wanted to use images as the test bed for developing and testing the initial framework of the distributed multimedia database. It should be pointed out here that both [5] as well as [6] can be used in the proposed framework without any loss of generality.…”

Section: Replicated Multidimensional Index Structurementioning

confidence: 99%

“…Though there are numerous multidimensional index structures such as those in [8] [3] that can handle the multidimensional aspect of the multimedia data but they lack the capability to handle the high-level semantic relationships efficiently. In our earlier works, we proposed multidimensional index structures including AH-Tree [4], HAH-Tree [5] and GeM-Tree [6] designed for efficient management of multimedia data comprising of images and videos. In this chapter, we extend the usability of multimedia index structures in a distributed Grid environment.…”

Section: Introductionmentioning

confidence: 99%

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A Distributed Multimedia Data Management over the Grid

Chatterjee

Sadjadi

Chen

2010

Multimedia Services in Intelligent Environments

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In this chapter, we propose a distributed multimedia data management architecture, which can efficiently store and retrieve multimedia data across several nodes of a Grid environment. The main components of the proposed system comprises of a distributed multidimensional index structure, a distributed query manager handling content-based information retrievals and a load balancing technology. The proposed distributed query manager embeds the high-level semantic relationships among the multimedia data objects into the k-NN based similarity search, thus bridging the semantic gap and increasing the relevance of query results manifold. This research has two major usabilities. First, it models a web environment where each node of the Grid can be considered as the nodes or sources of data in the world-wide-web. This should help to investigate and understand the challenges and requirements of future search paradigms based on content of multimedia data rather than on text annotations, as used currently. Second, it provides the foundation to develop content-based information retrievals as a possible Grid service. Extensive experiments were conducted with varied data sizes and different number of distribution nodes. Encouraging results are obtained that makes this endeavor a potential architecture to manage complex multimedia data over a distributed environment.

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Section: Replicated Multidimensional Index Structurementioning

confidence: 99%

Section: Replicated Multidimensional Index Structurementioning

confidence: 99%