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An Analytical Workflow for Clustering Forensic Images

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arxiv 2001.05845 v1 pith:O4H2V2LM submitted 2019-12-29 cs.CV

Sara Mousavi , Dylan Lee , Tatianna Griffin , Dawnie Steadman , Audris Mockus This is my paper · ORCID
classification cs.CV
keywords clusteringimagesworkflowforensiclargeadditionanalyticalclassic
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Large collections of images, if curated, drastically contribute to the quality of research in many domains. Unsupervised clustering is an intuitive, yet effective step towards curating such datasets. In this work, we present a workflow for unsupervisedly clustering a large collection of forensic images. The workflow utilizes classic clustering on deep feature representation of the images in addition to domain-related data to group them together. Our manual evaluation shows a purity of 89\% for the resulted clusters.

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