| dc.contributor | Olivares Poggi, Cesar Augusto | |
| dc.creator | Huiza Pereyra, Eric Raphael | |
| dc.date | 2020-09-01T00:12:05Z | |
| dc.date | 2020-09-01T00:12:05Z | |
| dc.date | 2020 | |
| dc.date | 2020-08-31 | |
| dc.identifier | http://hdl.handle.net/20.500.12404/16906 | |
| dc.description | 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. | |
| dc.description | Trabajo de investigación | |
| dc.format | application/pdf | |
| dc.language | eng | |
| dc.publisher | Pontificia Universidad Católica del Perú | |
| dc.publisher | PE | |
| dc.rights | Atribución 2.5 Perú | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.rights | http://creativecommons.org/licenses/by/2.5/pe/ | |
| dc.subject | Redes neuronales (Computación) | |
| dc.subject | Algoritmos computacionales | |
| dc.subject | Reconocimiento óptico de patrones | |
| dc.subject | https://purl.org/pe-repo/ocde/ford#1.02.00 | |
| dc.title | Talking with signs: a simple method to detect nouns and numbers in a non annotated signs language corpus | |
| dc.type | info:eu-repo/semantics/masterThesis | |
