Indoor human activity recognition with contextual cues in videos

Changmo Nam; Jun Cheol Park; Dae Shik Kim

doi:10.1145/2857546.2857645

Indoor human activity recognition with contextual cues in videos

Changmo Nam
, Jun Cheol Park
, Dae Shik Kim

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

4 Citations (Scopus)

Abstract

Nowadays researchers have been trying to recognize human activity using human joint information in RGB-D human activity dataset. However, it is necessary to recognize objects interacting with a human to improve human activity classification accuracy because an object is able to give us an important information to classify human activity. In this paper, we describe the effective way of detecting object region related to human activity. We used human joint information and its movement properties. The experimental result shows that object region interacting with a human is detected well by our proposed method.

Original language	English
Title of host publication	ACM IMCOM 2016
Subtitle of host publication	Proceedings of the 10th International Conference on Ubiquitous Information Management and Communication
Publisher	Association for Computing Machinery, Inc
ISBN (Electronic)	9781450341424
DOIs	https://doi.org/10.1145/2857546.2857645
Publication status	Published - 4 Jan 2016
Event	10th International Conference on Ubiquitous Information Management and Communication, IMCOM 2016 - Danang, Viet Nam Duration: 4 Jan 2016 → 6 Jan 2016

Publication series

Name	ACM IMCOM 2016: Proceedings of the 10th International Conference on Ubiquitous Information Management and Communication

Conference

Conference	10th International Conference on Ubiquitous Information Management and Communication, IMCOM 2016
Country/Territory	Viet Nam
City	Danang
Period	4/01/16 → 6/01/16

Bibliographical note

Publisher Copyright:
© 2016 ACM.

Keywords

Activity recognition
Object detection
Real-time object region detection

Access to Document

10.1145/2857546.2857645

Cite this

Nam, C., Park, J. C., & Kim, D. S. (2016). Indoor human activity recognition with contextual cues in videos. In ACM IMCOM 2016: Proceedings of the 10th International Conference on Ubiquitous Information Management and Communication Article a97 (ACM IMCOM 2016: Proceedings of the 10th International Conference on Ubiquitous Information Management and Communication). Association for Computing Machinery, Inc. https://doi.org/10.1145/2857546.2857645

Nam, Changmo ; Park, Jun Cheol ; Kim, Dae Shik. / Indoor human activity recognition with contextual cues in videos. ACM IMCOM 2016: Proceedings of the 10th International Conference on Ubiquitous Information Management and Communication. Association for Computing Machinery, Inc, 2016. (ACM IMCOM 2016: Proceedings of the 10th International Conference on Ubiquitous Information Management and Communication).

@inproceedings{35201bc7716c439388d98b72df92b517,

title = "Indoor human activity recognition with contextual cues in videos",

abstract = "Nowadays researchers have been trying to recognize human activity using human joint information in RGB-D human activity dataset. However, it is necessary to recognize objects interacting with a human to improve human activity classification accuracy because an object is able to give us an important information to classify human activity. In this paper, we describe the effective way of detecting object region related to human activity. We used human joint information and its movement properties. The experimental result shows that object region interacting with a human is detected well by our proposed method.",

keywords = "Activity recognition, Object detection, Real-time object region detection",

author = "Changmo Nam and Park, \{Jun Cheol\} and Kim, \{Dae Shik\}",

note = "Publisher Copyright: {\textcopyright} 2016 ACM.; 10th International Conference on Ubiquitous Information Management and Communication, IMCOM 2016 ; Conference date: 04-01-2016 Through 06-01-2016",

year = "2016",

month = jan,

day = "4",

doi = "10.1145/2857546.2857645",

language = "English",

series = "ACM IMCOM 2016: Proceedings of the 10th International Conference on Ubiquitous Information Management and Communication",

publisher = "Association for Computing Machinery, Inc",

booktitle = "ACM IMCOM 2016",

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Nam, C, Park, JC & Kim, DS 2016, Indoor human activity recognition with contextual cues in videos. in ACM IMCOM 2016: Proceedings of the 10th International Conference on Ubiquitous Information Management and Communication., a97, ACM IMCOM 2016: Proceedings of the 10th International Conference on Ubiquitous Information Management and Communication, Association for Computing Machinery, Inc, 10th International Conference on Ubiquitous Information Management and Communication, IMCOM 2016, Danang, Viet Nam, 4/01/16. https://doi.org/10.1145/2857546.2857645

Indoor human activity recognition with contextual cues in videos. / Nam, Changmo; Park, Jun Cheol; Kim, Dae Shik.
ACM IMCOM 2016: Proceedings of the 10th International Conference on Ubiquitous Information Management and Communication. Association for Computing Machinery, Inc, 2016. a97 (ACM IMCOM 2016: Proceedings of the 10th International Conference on Ubiquitous Information Management and Communication).

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

TY - GEN

T1 - Indoor human activity recognition with contextual cues in videos

AU - Nam, Changmo

AU - Park, Jun Cheol

AU - Kim, Dae Shik

PY - 2016/1/4

Y1 - 2016/1/4

N2 - Nowadays researchers have been trying to recognize human activity using human joint information in RGB-D human activity dataset. However, it is necessary to recognize objects interacting with a human to improve human activity classification accuracy because an object is able to give us an important information to classify human activity. In this paper, we describe the effective way of detecting object region related to human activity. We used human joint information and its movement properties. The experimental result shows that object region interacting with a human is detected well by our proposed method.

AB - Nowadays researchers have been trying to recognize human activity using human joint information in RGB-D human activity dataset. However, it is necessary to recognize objects interacting with a human to improve human activity classification accuracy because an object is able to give us an important information to classify human activity. In this paper, we describe the effective way of detecting object region related to human activity. We used human joint information and its movement properties. The experimental result shows that object region interacting with a human is detected well by our proposed method.

KW - Activity recognition

KW - Object detection

KW - Real-time object region detection

UR - https://www.scopus.com/pages/publications/84965043253

U2 - 10.1145/2857546.2857645

DO - 10.1145/2857546.2857645

M3 - Conference contribution

AN - SCOPUS:84965043253

T3 - ACM IMCOM 2016: Proceedings of the 10th International Conference on Ubiquitous Information Management and Communication

BT - ACM IMCOM 2016

PB - Association for Computing Machinery, Inc

T2 - 10th International Conference on Ubiquitous Information Management and Communication, IMCOM 2016

Y2 - 4 January 2016 through 6 January 2016

ER -

Nam C, Park JC, Kim DS. Indoor human activity recognition with contextual cues in videos. In ACM IMCOM 2016: Proceedings of the 10th International Conference on Ubiquitous Information Management and Communication. Association for Computing Machinery, Inc. 2016. a97. (ACM IMCOM 2016: Proceedings of the 10th International Conference on Ubiquitous Information Management and Communication). doi: 10.1145/2857546.2857645

Indoor human activity recognition with contextual cues in videos

Abstract

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Conference

Bibliographical note

Keywords

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