Abstract-We present an integrated framework for multimedia access and analysis of ancient Maya epigraphic resources, which is developed as an interdisciplinary effort involving epigraphers and computer scientists. Our work includes several contributions: definition of consistent conventions to generate high-quality representations of Maya hieroglyphs from the three most valuable ancient codices, currently residing in European museums and institutions; a digital repository system for glyph annotation and management; as well as automatic glyph retrieval and classification methods. We study the combination of statistical Maya language models and shape representation within a hieroglyph retrieval system, the impact of applying language models extracted from different hieroglyphic resources on various data types, and the effect of shape representation choices for glyph classification. A novel Maya hieroglyph dataset is contributed, which can be used for shape analysis benchmarks, and also to study the ancient Maya writing system.
Abstract. 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 given their visual complexity and large stylistic variety. More precisely, we demonstrate empirically that intermediate outputs of convolutional neural networks can be used as representations for complex shapes, even when their parameters are trained on gray-scale images, and that these representations can be more robust than traditional handcrafted features. We also show that it is possible to compress such representations up to only three dimensions without harming much of their discriminative structure, such that effective visualization of Maya hieroglyphs can be rendered for subsequent epigraphic analysis.
The present study deals with the mural of Structure B-XIII of the archaeological site of Uaxactun in Guatemala. Although this mural was found in 1937 and initially aroused much interest, it does not appear in recent works, given its destruction a few years after its discovery. Many new discoveries in the Maya area have been made and this old one has been burdened with interpretations that are far from the current state of the art. So, we have decided to reinitiate the investigation, digitally recreate the mural on the basis of photographs from the time of its discovery and reattempt to understand its meaning by analysing the image, hieroglyphic writing, and calendric record. We summarise the results and place these in a historical context that allows us to combine new mural data with those that we have obtained from the stone monuments of Uaxactun using modern technology. The results shed light on a critical period of Maya history shortly after the so-called Entrada associated with Teotihuacan.
Famous Uaxactun Mural paintings, which were found in Structure B-XIII, have been wellknown to Maya scholars for decades. They are considered as proof of Maya-Teotihuacan connection, and the importance of Uaxactun. On the other hand, the different scenes with musicians, nobles and warriors are beautiful source of Maya iconography. Below these paintings, also a short inscription in form of calendric notation was found. This inscription was not analyzed due to imperfect drawing, which was made by Antonio Tejeda in 1930's. Fortunately, it was possible to create a new rendering of this inscription, thanks to preserved photographs of Carnegie Institute.
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