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Título: Talking with signs: a simple method to detect nouns and numbers in a non annotated signs language corpus
Asesor(es): Olivares Poggi, Cesar Augusto
Campo OCDE: https://purl.org/pe-repo/ocde/ford#1.02.00
Fecha de publicación: 31-ago-2020
Institución: Pontificia Universidad Católica del Perú
Resumen: People with deafness or hearing disabilities who aim to use computer based systems rely on state-of-art video classification and human action recognition techniques that combine traditional movement pat-tern recognition and deep learning techniques. In this work we present a pipeline for semi-automatic video annotation applied to a non-annotated Peru-vian Signs Language (PSL) corpus along with a novel method for a progressive detection of PSL elements (nSDm). We produced a set of video annotations in-dicating signs appearances for a small set of nouns and numbers along with a labeled PSL dataset (PSL dataset). A model obtained after ensemble a 2D CNN trained with movement patterns extracted from the PSL dataset using Lucas Kanade Opticalflow, and a RNN with LSTM cells trained with raw RGB frames extracted from the PSL dataset reporting state-of-art results over the PSL dataset on signs classification tasks in terms of AUC, Precision and Recall.
Disciplina académico-profesional: Informática
Institución que otorga el grado o título: Pontificia Universidad Católica del Perú. Escuela de Posgrado
Grado o título: Maestro en Informática
Fecha de registro: 1-sep-2020; 1-sep-2020



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