Clothing Extremity Identification Using Convolutional Neural Network Regressor

Clothing Extremity Identification Using Convolutional Neural Network Regressor

Understanding and manipulating a textile objects with a high-dimensional configuration space in relation to its context poses a considerable challenge in the area of Robotics. One of the first step for manipulating textiles is to identify key grasping points on extremities such as collars and hem in...

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Bibliographic Details
Main Authors: Ngo, Genevieve C, Gaurav, Vishal, Shibata, Tomohiro
Format: text
Published: Archīum Ateneo 2018
Subjects:
Clothing
Extremities
Feature extraction
Robots
Convolutional neural networks
Task analysis
Textiles
Electrical and Computer Engineering
Fiber, Textile, and Weaving Arts
Online Access:https://archium.ateneo.edu/ecce-faculty-pubs/10
https://ieeexplore.ieee.org/abstract/document/8641046
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Institution: Ateneo De Manila University
Description
Summary:Understanding and manipulating a textile objects with a high-dimensional configuration space in relation to its context poses a considerable challenge in the area of Robotics. One of the first step for manipulating textiles is to identify key grasping points on extremities such as collars and hem in order to have a context-aware robotic grasping system. In this study, we proposed a method for identifying clothing extremity using a Convolutional Neural Network as a bounding box regression approach. Results indicate that the said method was able to identify and discriminate features of the collar while providing a high accuracy on identifying collar keypoints through a bounding box approach.

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