Straightforward Recognition of Daily Objects in Smart Environments from Wearable Vision Sensor

Javier Medina Quero; Federico Cruciani; Lorenzo Seidenari; Macarena Espinilla; CD Nugent

doi:10.1109/PERCOMW.2019.8730860

Straightforward Recognition of Daily Objects in Smart Environments from Wearable Vision Sensor

Javier Medina Quero, Federico Cruciani, Lorenzo Seidenari, Macarena Espinilla, CD Nugent

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

In this work, we propose a method to create and
synthesize a new set of virtual images of daily objects within
a smart environment partially automating the labeling process.
Proposed methods enable the generation of a large dataset
from a set of few images using an ad hoc data augmentation,
which increases the original dataset size, generating new items
through partial modification of available images. The proposed
method for data augmentation is accomplished through the
following steps: (i) object tracking is proposed to identify and
label static objects; and (ii) background subtraction is used to
select the masked foreground object of moving objects, which
are virtually projected with geometry transformation over room
images used as background. Furthermore, a case study is carried
out, where an inhabitant wears a wearable vision sensor in a daily
scene. Eight objects are learned using the proposed methodology.
Finally, obtained results and successful recognition rates are
discussed.

Original language	English
Title of host publication	2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019
Publisher	IEEE
Pages	46-51
Number of pages	6
ISBN (Electronic)	9781538691519
DOIs	https://doi.org/10.1109/PERCOMW.2019.8730860
Publication status	Published (in print/issue) - 6 Jun 2019
Event	2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019: PerCom Pervasive Computing 2019 - Kyoto, Japan Duration: 11 Mar 2019 → 15 Mar 2019 http://www.percom.org/Previous/ST2019/home.html

Conference

Conference	2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019
Abbreviated title	PerCom 2019
Country/Territory	Japan
City	Kyoto
Period	11/03/19 → 15/03/19
Internet address	http://www.percom.org/Previous/ST2019/home.html

Keywords

activity recognition
data augmentation
deep learning
object recognition
smart environments
wearable vision sensors

Access to Document

10.1109/PERCOMW.2019.8730860

Cite this

@inproceedings{31f259200b2441bd8d86f8202150a825,

title = "Straightforward Recognition of Daily Objects in Smart Environments from Wearable Vision Sensor",

abstract = "In this work, we propose a method to create andsynthesize a new set of virtual images of daily objects withina smart environment partially automating the labeling process.Proposed methods enable the generation of a large datasetfrom a set of few images using an ad hoc data augmentation,which increases the original dataset size, generating new itemsthrough partial modification of available images. The proposedmethod for data augmentation is accomplished through thefollowing steps: (i) object tracking is proposed to identify andlabel static objects; and (ii) background subtraction is used toselect the masked foreground object of moving objects, whichare virtually projected with geometry transformation over roomimages used as background. Furthermore, a case study is carriedout, where an inhabitant wears a wearable vision sensor in a dailyscene. Eight objects are learned using the proposed methodology.Finally, obtained results and successful recognition rates arediscussed.",

keywords = "activity recognition, data augmentation, deep learning, object recognition, smart environments, wearable vision sensors",

author = "Quero, {Javier Medina} and Federico Cruciani and Lorenzo Seidenari and Macarena Espinilla and CD Nugent",

year = "2019",

month = jun,

day = "6",

doi = "10.1109/PERCOMW.2019.8730860",

language = "English",

pages = "46--51",

booktitle = "2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019",

publisher = "IEEE",

address = "United States",

note = "2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019 : PerCom Pervasive Computing 2019, PerCom 2019 ; Conference date: 11-03-2019 Through 15-03-2019",

url = "http://www.percom.org/Previous/ST2019/home.html",

}

Quero, JM, Cruciani, F, Seidenari, L, Espinilla, M & Nugent, CD 2019, Straightforward Recognition of Daily Objects in Smart Environments from Wearable Vision Sensor. in 2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019., 8730860, IEEE, pp. 46-51, 2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019, Kyoto, Japan, 11/03/19. https://doi.org/10.1109/PERCOMW.2019.8730860

Straightforward Recognition of Daily Objects in Smart Environments from Wearable Vision Sensor. / Quero, Javier Medina; Cruciani, Federico; Seidenari, Lorenzo et al.
2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019. IEEE, 2019. p. 46-51 8730860.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Straightforward Recognition of Daily Objects in Smart Environments from Wearable Vision Sensor

AU - Quero, Javier Medina

AU - Cruciani, Federico

AU - Seidenari, Lorenzo

AU - Espinilla, Macarena

AU - Nugent, CD

PY - 2019/6/6

Y1 - 2019/6/6

N2 - In this work, we propose a method to create andsynthesize a new set of virtual images of daily objects withina smart environment partially automating the labeling process.Proposed methods enable the generation of a large datasetfrom a set of few images using an ad hoc data augmentation,which increases the original dataset size, generating new itemsthrough partial modification of available images. The proposedmethod for data augmentation is accomplished through thefollowing steps: (i) object tracking is proposed to identify andlabel static objects; and (ii) background subtraction is used toselect the masked foreground object of moving objects, whichare virtually projected with geometry transformation over roomimages used as background. Furthermore, a case study is carriedout, where an inhabitant wears a wearable vision sensor in a dailyscene. Eight objects are learned using the proposed methodology.Finally, obtained results and successful recognition rates arediscussed.

AB - In this work, we propose a method to create andsynthesize a new set of virtual images of daily objects withina smart environment partially automating the labeling process.Proposed methods enable the generation of a large datasetfrom a set of few images using an ad hoc data augmentation,which increases the original dataset size, generating new itemsthrough partial modification of available images. The proposedmethod for data augmentation is accomplished through thefollowing steps: (i) object tracking is proposed to identify andlabel static objects; and (ii) background subtraction is used toselect the masked foreground object of moving objects, whichare virtually projected with geometry transformation over roomimages used as background. Furthermore, a case study is carriedout, where an inhabitant wears a wearable vision sensor in a dailyscene. Eight objects are learned using the proposed methodology.Finally, obtained results and successful recognition rates arediscussed.

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M3 - Conference contribution

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ER -

Straightforward Recognition of Daily Objects in Smart Environments from Wearable Vision Sensor

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Keywords

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