![]() Shape matching and object recognition using shape contexts. neural information processing systems, Denver, pp. 831–837.īelongie, S., Malik, J., & Puzicha, J. Shape context: a new descriptor for shape matching and object recognition. Reading: Addison Wesley.īelongie, S., Malik, J., & Puzicha, J. Overall, our approach is promising, as it improves performance on the retrieval task, has been successfully validated under an epigraphic viewpoint, and has the potential of offering both novel insights in archeology and practical solutions for real daily scholar needs.īaeza-Yates, R., & Ribeiro-Neto, B. ![]() Third, we present what to our knowledge constitutes the first automatic analysis of visual variability of syllabic glyphs along historical periods and across geographic regions of the ancient Maya world via the HOOSC descriptor. Based on the identification of their limitations, we propose a new shape descriptor named Histogram of Orientation Shape Context (HOOSC), which is more robust and suitable for description of Maya hieroglyphs. Second, we present an objective evaluation of the performance of two state-of-the-art shape-based contextual descriptors (Shape Context and Generalized Shape Context) in retrieval tasks, using two datasets of syllabic Maya glyphs. First, we introduce an overview of our interdisciplinary approach towards the improvement of the documentation, analysis, and preservation of Maya pictographic data. ![]() ![]() Our work is guided by realistic needs of archaeologists and scholars who critically need support for search and retrieval tasks in large Maya imagery collections. This paper presents an original approach for shape-based analysis of ancient Maya hieroglyphs based on an interdisciplinary collaboration between computer vision and archeology. ![]()
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