Retrieval of Images with Objects of Specific Size, Location, and Spatial Configuration

Pourian, Niloufar; Manjunath, B.S.

doi:10.1109/wacv.2015.133

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Graph Structure: Single Modality1

Community Detection: Single Modality1

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Cited by 2 publications

(2 citation statements)

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“…Following the work of [21,22], we integrate the visual characteristics along with the spatial information of image-parts across all database images in a graph structure. To provide spatial information, we utilize a segmentation algorithm based on color and texture [23].…”

Section: Graph Structure: Single Modalitymentioning

confidence: 99%

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Search and retrieval of multi-modal data associated with image-parts

Pourian

Karthikeyan

Manjunath

2015

2015 IEEE International Conference on Image Processing (ICIP)

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We present a novel framework for querying multi-modal data from a heterogeneous database containing images, textual tags, and GPS coordinates. We construct a bi-layer graph structure using localized image-parts and associated GPS locations and textual tags from the database. The first layer graphs capture similar data points from a single modality using a spectral clustering algorithm. The second layer of our multi-modal network allows one to integrate the relationships between clusters of different modalities. The proposed network model enables us to use flexible multi-modal queries on the database.

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Section: Graph Structure: Single Modalitymentioning

confidence: 99%

“…For example, in the graphical image structure, each community contains all the pieces/image-parts of an object and mapping these back to each segmented image would highlight/detect that particular object [21,22]. A detected community for the textual tags' graph corresponds to highly related/correlated tags.…”

Section: Community Detection: Single Modalitymentioning

confidence: 99%