Real-life activity recognition: Recognizing reading activities

Kai Kunze

doi:10.1145/2516911.2516912

Real-life activity recognition: Recognizing reading activities

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

Abstract

How can we extract high level information about human actions and complex real world situations from heterogeneous ensembles of simple, often unreliable sensors embedded in commodity devices? We focus on how to use body-worn devices for activity recognition in general, and how to combine them with infrastructure sensing. We discuss how to combine them with traditional computer vision approaches for a specific high level human activity, namely knowledge acquisition (in particular recognizing reading activities).

Original language	English
Title of host publication	Joint Proc. of the Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd IJCAI 2013
Number of pages	1
DOIs	https://doi.org/10.1145/2516911.2516912
Publication status	Published - 2013 Dec 31
Externally published	Yes
Event	Joint Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd Int. Joint Conf. on Artificial Intelligence, IJCAI 2013 - Beijing, China Duration: 2013 Aug 4 → 2013 Aug 5

Publication series

Name	ACM International Conference Proceeding Series

Other

Other	Joint Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd Int. Joint Conf. on Artificial Intelligence, IJCAI 2013
Country	China
City	Beijing
Period	13/8/4 → 13/8/5

Keywords

activity recognition
reading behavior
robust

ASJC Scopus subject areas

Software
Human-Computer Interaction
Computer Vision and Pattern Recognition
Computer Networks and Communications

Access to Document

10.1145/2516911.2516912

Fingerprint Dive into the research topics of 'Real-life activity recognition: Recognizing reading activities'. Together they form a unique fingerprint.

Cite this

Kunze, K. (2013). Real-life activity recognition: Recognizing reading activities. In Joint Proc. of the Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd IJCAI 2013 (ACM International Conference Proceeding Series). https://doi.org/10.1145/2516911.2516912

Real-life activity recognition : Recognizing reading activities. / Kunze, Kai.

Joint Proc. of the Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd IJCAI 2013. 2013. (ACM International Conference Proceeding Series).

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

Kunze, K 2013, Real-life activity recognition: Recognizing reading activities. in Joint Proc. of the Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd IJCAI 2013. ACM International Conference Proceeding Series, Joint Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd Int. Joint Conf. on Artificial Intelligence, IJCAI 2013, Beijing, China, 13/8/4. https://doi.org/10.1145/2516911.2516912

@inproceedings{36e024b12c3849e1bf2820448002acd1,

title = "Real-life activity recognition: Recognizing reading activities",

abstract = "How can we extract high level information about human actions and complex real world situations from heterogeneous ensembles of simple, often unreliable sensors embedded in commodity devices? We focus on how to use body-worn devices for activity recognition in general, and how to combine them with infrastructure sensing. We discuss how to combine them with traditional computer vision approaches for a specific high level human activity, namely knowledge acquisition (in particular recognizing reading activities).",

keywords = "activity recognition, reading behavior, robust",

author = "Kai Kunze",

year = "2013",

month = dec,

day = "31",

doi = "10.1145/2516911.2516912",

language = "English",

isbn = "9781450323468",

series = "ACM International Conference Proceeding Series",

booktitle = "Joint Proc. of the Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd IJCAI 2013",

note = "Joint Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd Int. Joint Conf. on Artificial Intelligence, IJCAI 2013 ; Conference date: 04-08-2013 Through 05-08-2013",

}

TY - GEN

T1 - Real-life activity recognition

T2 - Joint Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd Int. Joint Conf. on Artificial Intelligence, IJCAI 2013

AU - Kunze, Kai

PY - 2013/12/31

Y1 - 2013/12/31

N2 - How can we extract high level information about human actions and complex real world situations from heterogeneous ensembles of simple, often unreliable sensors embedded in commodity devices? We focus on how to use body-worn devices for activity recognition in general, and how to combine them with infrastructure sensing. We discuss how to combine them with traditional computer vision approaches for a specific high level human activity, namely knowledge acquisition (in particular recognizing reading activities).

AB - How can we extract high level information about human actions and complex real world situations from heterogeneous ensembles of simple, often unreliable sensors embedded in commodity devices? We focus on how to use body-worn devices for activity recognition in general, and how to combine them with infrastructure sensing. We discuss how to combine them with traditional computer vision approaches for a specific high level human activity, namely knowledge acquisition (in particular recognizing reading activities).

KW - activity recognition

KW - reading behavior

KW - robust

UR - http://www.scopus.com/inward/record.url?scp=84891107778&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84891107778&partnerID=8YFLogxK

U2 - 10.1145/2516911.2516912

DO - 10.1145/2516911.2516912

M3 - Conference contribution

AN - SCOPUS:84891107778

SN - 9781450323468

T3 - ACM International Conference Proceeding Series

BT - Joint Proc. of the Workshop on AI Problems and Approaches for Intelligent Environments, AI@IE 2013 and Workshop on Semantic Cities, SemCities 2013 - In Conj. with the 23rd IJCAI 2013

Y2 - 4 August 2013 through 5 August 2013

ER -