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Determining Interacting Objects in Human-Centric Activities via Qualitative Spatio-Temporal Reasoning

Sokeh, Hajar; Gould, Stephen; Renz, Jochen

Description

Understanding the activities taking place in a video is a challenging problem in Artificial Intelligence. Complex video sequences contain many activities and involve a multitude of interacting objects. Determining which objects are relevant to a particular activity is the first step in understanding the activity. Indeed many objects in the scene are irrelevant to the main activity taking place. In this work, we consider human-centric activities and look to identify which objects in the scene...[Show more]

dc.contributor.authorSokeh, Hajar
dc.contributor.authorGould, Stephen
dc.contributor.authorRenz, Jochen
dc.coverage.spatialSingapore
dc.date.accessioned2016-06-14T23:21:12Z
dc.date.createdNovember 1-5 2014
dc.identifier.isbn9783319168135
dc.identifier.urihttp://hdl.handle.net/1885/103763
dc.description.abstractUnderstanding the activities taking place in a video is a challenging problem in Artificial Intelligence. Complex video sequences contain many activities and involve a multitude of interacting objects. Determining which objects are relevant to a particular activity is the first step in understanding the activity. Indeed many objects in the scene are irrelevant to the main activity taking place. In this work, we consider human-centric activities and look to identify which objects in the scene are involved in the activity. We take an activity-agnostic approach and rank every moving object in the scene with how likely it is to be involved in the activity. We use a comprehensive spatio-temporal representation that captures the joint movement between humans and each object. We then use supervised machine learning techniques to recognize relevant objects based on these features. Our approach is tested on the challenging Mind’s Eye dataset.
dc.publisherSpringer
dc.relation.ispartofseries12th Asian Conference on Computer Vision, ACCV 2014
dc.sourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.titleDetermining Interacting Objects in Human-Centric Activities via Qualitative Spatio-Temporal Reasoning
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2015
local.identifier.absfor080602 - Computer-Human Interaction
local.identifier.ariespublicationu4334215xPUB1461
local.type.statusPublished Version
local.contributor.affiliationSokeh, Hajar, College of Engineering and Computer Science, ANU
local.contributor.affiliationGould, Stephen, College of Engineering and Computer Science, ANU
local.contributor.affiliationRenz, Jochen, College of Engineering and Computer Science, ANU
local.description.embargo2037-12-31
local.bibliographicCitation.startpage550
local.bibliographicCitation.lastpage563
local.identifier.doi10.1007/978-3-319-16814-2_36
local.identifier.absseo970108 - Expanding Knowledge in the Information and Computing Sciences
dc.date.updated2016-06-14T09:02:40Z
local.identifier.scopusID2-s2.0-84929630645
CollectionsANU Research Publications

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