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portada ٍSocial Touch Gesture Recognition using Convolution Neural Nrtwork
Type
Physical Book
Author
Publisher
Language
English
Pages
136
Format
Paperback
Dimensions
22.9 x 15.2 x 0.8 cm
Weight
0.21 kg.
ISBN13
9786200066862
Categories

ٍSocial Touch Gesture Recognition using Convolution Neural Nrtwork

Saad Albawi (Author) · Noor Publishing · Paperback

ٍSocial Touch Gesture Recognition using Convolution Neural Nrtwork - Albawi, Saad

New Book Imported to Taiwan
Delivery: 17 Sep - 25 Sep Shipping: 13 to 14 business days.
NT$ 1,285
NT$ 1,285

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Synopsis "ٍSocial Touch Gesture Recognition using Convolution Neural Nrtwork"

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.

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