%0 Generic
%T Word separation in continuous sign language using isolated signs and post-processing
%A Razieh Rastgoo
%A Kourosh Kiani
%A Sergio Escalera
%D 2022
%F Razieh Rastgoo2022
%O HUPBA; no menciona
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=3824), last updated on Thu, 27 Apr 2023 13:28:50 +0200
%X Continuous Sign Language Recognition (CSLR) is a long challenging task in Computer Vision due to the difficulties in detecting the explicit boundaries between the words in a sign sentence. To deal with this challenge, we propose a two-stage model. In the first stage, the predictor model, which includes a combination of CNN, SVD, and LSTM, is trained with the isolated signs. In the second stage, we apply a post-processing algorithm to the Softmax outputs obtained from the first part of the model in order to separate the isolated signs in the continuous signs. Due to the lack of a large dataset, including both the sign sequences and the corresponding isolated signs, two public datasets in Isolated Sign Language Recognition (ISLR), RKS-PERSIANSIGN and ASLVID, are used for evaluation. Results of the continuous sign videos confirm the efficiency of the proposed model to deal with isolated sign boundaries detection.
%9 miscellaneous
%U http://refbase.cvc.uab.es/files/RKE2022b.pdf