Handwritten Text Retrieval from Unlabeled Collections
Santhoshini Gongidi and C.V. Jawahar
Handwritten documents from communities like cultural heritage, judiciary, and modern journals remain largely unexplored even today. To a great extent, this is due to the lack of retrieval tools for such unlabeled document collections. In this work, we consider such collections and present a simple, robust retrieval framework for easy information access. We achieve retrieval on unlabeled novel collections through invariant features learnt for handwritten text. These feature representations enable zero-shot retrieval for novel queries on unexplored collections. We improve the framework further by supporting search via text and exemplar queries. Four new collections written in English, Malayalam, and Bengali are used to evaluate our text retrieval framework. These collections comprise 2957 handwritten pages and over 300K words. We report promising results on these collections, despite the zero-shot constraint and huge collection size. Our framework allows the addition of new collections without any need for specific finetuning or labeling. Finally, we also present a demonstration of the retrieval framework.
Demo link: HW-Search
Santhoshini Gongidi, C V Jawahar, Handwritten Text Retrieval from Unlabeled Collections, CVIP 2021
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