Name: ٍSocial Touch Gesture Recognition using Convolution Neural Nrtwork (en Inglés)
Price: 49.63 USD
Availability: InStock
Author: Albawi, Saad
ISBN: 9786200066862

portada ٍSocial Touch Gesture Recognition using Convolution Neural Nrtwork (en Inglés)

ٍSocial Touch Gesture Recognition using Convolution Neural Nrtwork (en Inglés)

Formato

Libro Físico

Autor

Saad Albawi

Editorial

Noor Publishing

Idioma

Inglés

N° páginas

136

Encuadernación

Tapa Blanda

Dimensiones

22.9 x 15.2 x 0.8 cm

Peso

0.21 kg.

ISBN13

9786200066862

Categorías

Tecnología de la información: cuestiones generales

ٍSocial Touch Gesture Recognition using Convolution Neural Nrtwork (en Inglés)

Saad Albawi (Autor) · Noor Publishing · Tapa Blanda

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Reseña del libro "ٍSocial Touch Gesture Recognition using Convolution Neural Nrtwork (en Inglés)"

Recently, social touch gesture recognition has been considered an important topic for touch modality, which can lead to highly efficient and realistic human-robot interaction. In this paper, a deep convolutional neural network is selected to implement a social touch recognition system for raw input samples (sensor data) only. The touch gesture recognition is performed using a dataset previously measured with numerous subjects that perform varying social gestures. This dataset is dubbed as the corpus of social touch, where touch was performed on a mannequin arm. A leave-one-subject-out cross-validation method is used to evaluate system performance. The proposed method can recognize gestures in nearly real time after acquiring a minimum number of frames (the average range of frame length was from 0.2% to 4.19 % from the original frame lengths) with a classification accuracy of 63.7%. The achieved classification accuracy is competitive in terms of the performance of existing algorithms. Furthermore, the proposed system outperforms other classification algorithms in terms of classification ratio and touch recognition time without data preprocessing for the same dataset.