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A Global-Local Approach to Extracting Deformable Fashion Items from Web Images Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Learning to Recognize Hand-Held Objects from Scratch

Authors : Xue Li, Shuqiang Jiang, Xiong Lv, Chengpeng Chen

Published in: Advances in Multimedia Information Processing - PCM 2016

Publisher: Springer International Publishing

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Abstract

Real-life environments are open-ended and dynamic: unlearned information comes over time. These changes of environments ask for the systems to have the ability of self growth. A reasonable solution is to build an intelligent human-computer interaction system to simulate the mind at birth, and then automatically teach it by human. In this work, we present a hand-held object recognition system which could incrementally enhance its recognition ability from beginning during the interaction with humans. Automatically capturing the images of hand-held objects and the voice of users, our system could refer the interacting person as a strong teacher. This allows the system to learn from scratch and to learn new concepts one after another like humans. Although our system is implemented on hand-held recognition scenario, we also implement experiments on ImageNet dataset to validate the effectiveness of our system. Experimental results illustrate its performance.

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Metadata
Title
Learning to Recognize Hand-Held Objects from Scratch
Authors
Xue Li
Shuqiang Jiang
Xiong Lv
Chengpeng Chen
Copyright Year
2016
Book
Advances in Multimedia Information Processing - PCM 2016

Print ISBN: 978-3-319-48895-0

Electronic ISBN: 978-3-319-48896-7

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-48896-7_52