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Publikationer från KTH
Conference object . 2013 . Peer-reviewed
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https://doi.org/10.1109/cvpr.2...
Article . 2013 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object . 2023
Data sources: DBLP
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Decoding Children's Social Behavior

Authors: James M. Rehg; Gregory D. Abowd; Agata Rozga; Mario Romero; Mark A. Clements; Stan Sclaroff; Irfan A. Essa; +10 Authors

Decoding Children's Social Behavior

Abstract

We introduce a new problem domain for activity recognition: the analysis of children's social and communicative behaviors based on video and audio data. We specifically target interactions between children aged 1-2 years and an adult. Such interactions arise naturally in the diagnosis and treatment of developmental disorders such as autism. We introduce a new publicly-available dataset containing over 160 sessions of a 3-5 minute child-adult interaction. In each session, the adult examiner followed a semi-structured play interaction protocol which was designed to elicit a broad range of social behaviors. We identify the key technical challenges in analyzing these behaviors, and describe methods for decoding the interactions. We present experimental results that demonstrate the potential of the dataset to drive interesting research questions, and show preliminary results for multi-modal activity recognition.

Countries
Italy, Sweden
Keywords

Behavior, Psychology, Dataset, Video analysis, Speech Analysis, Autism, Behavior, Inter-action protocols, Social and communicative behavior, Autism, Developmental disorders, Video analysis, Annan data- och informationsvetenskap, Semi-structured, Speech Analysis, Research questions, Technical challenges, Activity recognition, Psychology, Social behavior, Other Computer and Information Science, Dataset

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    103
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
103
Top 10%
Top 1%
Top 1%
Green
bronze