EPIC-Tent: An Egocentric Video Dataset for Camping Tent Assembly

Youngkyoon Jang; Brian T Sullivan; Casimir J H Ludwig; Iain D Gilchrist; Dima Damen; Walterio W Mayol-Cuevas

EPIC-Tent: An Egocentric Video Dataset for Camping Tent Assembly

Youngkyoon Jang, Brian T Sullivan, Casimir J H Ludwig, Iain D Gilchrist, Dima Damen, Walterio W Mayol-Cuevas

Research output: Contribution to conference › Conference Paper › peer-review

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Abstract

This paper presents an outdoor video dataset annotated with action labels, collected from 24 participants wearing two head-mounted cameras (GoPro and SMI eye tracker) while assembling a camping tent. In total, this is 5.4 hours of recordings. Tent assembly includes manual interactions with non-rigid objects such as spreading the tent, securing guylines, reading instructions, and opening a tent bag. An interesting aspect of the dataset is that it reflects participants' proficiency in completing or understanding the task. This leads to participant differences in action sequences and action durations. Our dataset, called EPIC-Tent, also has several new types of annotations for two synchronised egocentric videos. These include task errors, self-rated uncertainty and gaze position, in addition to the task action labels. We present baseline results on the EPIC-Tent dataset using a state-of-the-art method for offline and online action recognition and detection.

Original language	English
Number of pages	9
Publication status	Published - 2 Nov 2019
Event	The Fifth International Workshop on Egocentric Perception, Interaction and Computing - Seoul, Korea, Republic of Duration: 2 Nov 2019 → 2 Nov 2019 Conference number: 5 https://eyewear-computing.org/EPIC_ICCV19/

Conference

Conference	The Fifth International Workshop on Egocentric Perception, Interaction and Computing
Abbreviated title	EPIC@ICCV19
Country/Territory	Korea, Republic of
City	Seoul
Period	2/11/19 → 2/11/19
Internet address	https://eyewear-computing.org/EPIC_ICCV19/

Research Groups and Themes

Visual Perception

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EPIC-Tent
Mayol-Cuevas, W. (Creator), Aldamen, D. (Creator), Jang, Y. (Creator), Sullivan, B. (Creator), Gilchrist, I. (Creator) & Ludwig, C. (Creator), University of Bristol, 17 Jun 2020
DOI: 10.5523/bris.2ite3tu1u53n42hjfh3886sa86, http://data.bris.ac.uk/data/dataset/2ite3tu1u53n42hjfh3886sa86
Dataset

Cite this

@conference{4040b85671344b558227b97540b73439,

title = "EPIC-Tent: An Egocentric Video Dataset for Camping Tent Assembly",

abstract = "This paper presents an outdoor video dataset annotated with action labels, collected from 24 participants wearing two head-mounted cameras (GoPro and SMI eye tracker) while assembling a camping tent. In total, this is 5.4 hours of recordings. Tent assembly includes manual interactions with non-rigid objects such as spreading the tent, securing guylines, reading instructions, and opening a tent bag. An interesting aspect of the dataset is that it reflects participants' proficiency in completing or understanding the task. This leads to participant differences in action sequences and action durations. Our dataset, called EPIC-Tent, also has several new types of annotations for two synchronised egocentric videos. These include task errors, self-rated uncertainty and gaze position, in addition to the task action labels. We present baseline results on the EPIC-Tent dataset using a state-of-the-art method for offline and online action recognition and detection.",

author = "Youngkyoon Jang and Sullivan, \{Brian T\} and Ludwig, \{Casimir J H\} and Gilchrist, \{Iain D\} and Dima Damen and Mayol-Cuevas, \{Walterio W\}",

year = "2019",

month = nov,

day = "2",

language = "English",

note = "The Fifth International Workshop on Egocentric Perception, Interaction and Computing, EPIC@ICCV19 ; Conference date: 02-11-2019 Through 02-11-2019",

url = "https://eyewear-computing.org/EPIC\_ICCV19/",

}

TY - CONF

T1 - EPIC-Tent

T2 - The Fifth International Workshop on Egocentric Perception, Interaction and Computing

AU - Jang, Youngkyoon

AU - Sullivan, Brian T

AU - Ludwig, Casimir J H

AU - Gilchrist, Iain D

AU - Damen, Dima

AU - Mayol-Cuevas, Walterio W

N1 - Conference code: 5

PY - 2019/11/2

Y1 - 2019/11/2

N2 - This paper presents an outdoor video dataset annotated with action labels, collected from 24 participants wearing two head-mounted cameras (GoPro and SMI eye tracker) while assembling a camping tent. In total, this is 5.4 hours of recordings. Tent assembly includes manual interactions with non-rigid objects such as spreading the tent, securing guylines, reading instructions, and opening a tent bag. An interesting aspect of the dataset is that it reflects participants' proficiency in completing or understanding the task. This leads to participant differences in action sequences and action durations. Our dataset, called EPIC-Tent, also has several new types of annotations for two synchronised egocentric videos. These include task errors, self-rated uncertainty and gaze position, in addition to the task action labels. We present baseline results on the EPIC-Tent dataset using a state-of-the-art method for offline and online action recognition and detection.

AB - This paper presents an outdoor video dataset annotated with action labels, collected from 24 participants wearing two head-mounted cameras (GoPro and SMI eye tracker) while assembling a camping tent. In total, this is 5.4 hours of recordings. Tent assembly includes manual interactions with non-rigid objects such as spreading the tent, securing guylines, reading instructions, and opening a tent bag. An interesting aspect of the dataset is that it reflects participants' proficiency in completing or understanding the task. This leads to participant differences in action sequences and action durations. Our dataset, called EPIC-Tent, also has several new types of annotations for two synchronised egocentric videos. These include task errors, self-rated uncertainty and gaze position, in addition to the task action labels. We present baseline results on the EPIC-Tent dataset using a state-of-the-art method for offline and online action recognition and detection.

M3 - Conference Paper

Y2 - 2 November 2019 through 2 November 2019

ER -

EPIC-Tent: An Egocentric Video Dataset for Camping Tent Assembly

Abstract

Conference

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Datasets

EPIC-Tent

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