Parsing activity into meaningful events

Jeffrey M. Zacks

doi:10.1109/ROMAN.2005.1513778

Parsing activity into meaningful events

Jeffrey M. Zacks

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

1 Scopus citations

Abstract

People segment ongoing activity into meaningful events, which has important implications for memory and planning. Movement is one basis for segmentation. Perceptual experiments show that movement features are correlated with participants' segmentation of simple events. Neuroimaging data show that regions motion processing regions transiently increase activity at natural event boundaries. The strong relationships between movement and event segmentation may prove helpful for human-robot interaction. It may be possible for computational vision systems to automatically segment ongoing activity into meaningful units, such that those units can be used as the input to algorithms for recognizing the significance of a partner's actions.

Original language	English
Title of host publication	14th IEEE Workshop on Robot and Human Interactive Communication, RO-MAN 2005
Pages	190-195
Number of pages	6
DOIs	https://doi.org/10.1109/ROMAN.2005.1513778
State	Published - 2005
Event	14th IEEE Workshop on Robot and Human Interactive Communication, RO-MAN 2005 - Nashville, TN, United States Duration: Aug 13 2005 → Aug 15 2005

Publication series

Name	Proceedings - IEEE International Workshop on Robot and Human Interactive Communication
Volume	2005

Conference

Conference	14th IEEE Workshop on Robot and Human Interactive Communication, RO-MAN 2005
Country/Territory	United States
City	Nashville, TN
Period	08/13/05 → 08/15/05

Keywords

Cognition
Event perception
Motion processing
Segmentation

Access to Document

10.1109/ROMAN.2005.1513778

Cite this

@inproceedings{548a749400f34646acc1a6d04500cb41,

title = "Parsing activity into meaningful events",

abstract = "People segment ongoing activity into meaningful events, which has important implications for memory and planning. Movement is one basis for segmentation. Perceptual experiments show that movement features are correlated with participants' segmentation of simple events. Neuroimaging data show that regions motion processing regions transiently increase activity at natural event boundaries. The strong relationships between movement and event segmentation may prove helpful for human-robot interaction. It may be possible for computational vision systems to automatically segment ongoing activity into meaningful units, such that those units can be used as the input to algorithms for recognizing the significance of a partner's actions.",

keywords = "Cognition, Event perception, Motion processing, Segmentation",

author = "Zacks, {Jeffrey M.}",

year = "2005",

doi = "10.1109/ROMAN.2005.1513778",

language = "English",

isbn = "0780392752",

series = "Proceedings - IEEE International Workshop on Robot and Human Interactive Communication",

pages = "190--195",

booktitle = "14th IEEE Workshop on Robot and Human Interactive Communication, RO-MAN 2005",

note = "14th IEEE Workshop on Robot and Human Interactive Communication, RO-MAN 2005 ; Conference date: 13-08-2005 Through 15-08-2005",

}

Zacks, JM 2005, Parsing activity into meaningful events. in 14th IEEE Workshop on Robot and Human Interactive Communication, RO-MAN 2005., 1513778, Proceedings - IEEE International Workshop on Robot and Human Interactive Communication, vol. 2005, pp. 190-195, 14th IEEE Workshop on Robot and Human Interactive Communication, RO-MAN 2005, Nashville, TN, United States, 08/13/05. https://doi.org/10.1109/ROMAN.2005.1513778

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T1 - Parsing activity into meaningful events

AU - Zacks, Jeffrey M.

PY - 2005

Y1 - 2005

N2 - People segment ongoing activity into meaningful events, which has important implications for memory and planning. Movement is one basis for segmentation. Perceptual experiments show that movement features are correlated with participants' segmentation of simple events. Neuroimaging data show that regions motion processing regions transiently increase activity at natural event boundaries. The strong relationships between movement and event segmentation may prove helpful for human-robot interaction. It may be possible for computational vision systems to automatically segment ongoing activity into meaningful units, such that those units can be used as the input to algorithms for recognizing the significance of a partner's actions.

AB - People segment ongoing activity into meaningful events, which has important implications for memory and planning. Movement is one basis for segmentation. Perceptual experiments show that movement features are correlated with participants' segmentation of simple events. Neuroimaging data show that regions motion processing regions transiently increase activity at natural event boundaries. The strong relationships between movement and event segmentation may prove helpful for human-robot interaction. It may be possible for computational vision systems to automatically segment ongoing activity into meaningful units, such that those units can be used as the input to algorithms for recognizing the significance of a partner's actions.

KW - Cognition

KW - Event perception

KW - Motion processing

KW - Segmentation

UR - http://www.scopus.com/inward/record.url?scp=33746599492&partnerID=8YFLogxK

U2 - 10.1109/ROMAN.2005.1513778

DO - 10.1109/ROMAN.2005.1513778

M3 - Conference contribution

AN - SCOPUS:33746599492

SN - 0780392752

SN - 9780780392755

T3 - Proceedings - IEEE International Workshop on Robot and Human Interactive Communication

SP - 190

EP - 195

BT - 14th IEEE Workshop on Robot and Human Interactive Communication, RO-MAN 2005

T2 - 14th IEEE Workshop on Robot and Human Interactive Communication, RO-MAN 2005

Y2 - 13 August 2005 through 15 August 2005

ER -

Parsing activity into meaningful events

Abstract

Publication series

Conference

Keywords

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