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We analyze the performance of deep neural architectures for extracting shape representations of binary images, and for generating low-dimensional representations of them. In particular, we focus on indexing binary images exhibiting compounds of Maya hieroglyphic signs, referred to as glyph-blocks, which constitute a very challenging dataset of arts...
This article presents an integrated framework for multimedia access and analysis of ancient Maya epigraphic resources, which is developed as an interdisciplinary effort involving epigraphers (someone who deciphers ancient inscriptions) and computer scientists. Our work includes several contributions: a definition of consistent conventions to genera...
We propose an automatic Maya hieroglyph retrieval method integrating shape and glyph context information. Two recent local shape descriptors, Gradient Field Histogram of Orientation Gradient (GF-HOG) and Histogram of Orientation Shape Context (HOOSC), are evaluated. To encode the context information, we propose to convert each Maya glyph block into...
We present an overview of the MAAYA project (http://www.idiap.ch/project/maaya/), an interdisciplinary effort integrating the work of epigraphists and computer scientists with three goals: (1) Design and development of computational tools for visual analysis and information management that effectively support the work of Maya hieroglyphic scholars;...