6533b82efe1ef96bd1292934

RESEARCH PRODUCT

Decoding Children's Social Behavior

Jianming ZhangOpal Y. OusleyZhefan YeJames M. RehgChanho KimYin LiMark A. ClementsJonathan C. KimJonathan BidwellLiliana Lo PrestiHrishikesh RaoIrfan EssaStan SclaroffDenis LantsmanGregory D. AbowdAgata RozgaMario Romero

subject

Behavior Psychology Dataset Video analysis Speech Analysis AutismInter-action protocolsSocial and communicative behaviorInteraction protocol02 engineering and technologycomputer.software_genreAnnan data- och informationsvetenskapSession (web analytics)Activity recognitionTechnical challenges0202 electrical engineering electronic engineering information engineeringmedicineSocial behaviorAudio signal processingMultimediabusiness.industryDevelopmental disorders020207 software engineeringmedicine.diseaseSemi-structuredResearch questionsActivity recognitionProblem domainKey (cryptography)Autism020201 artificial intelligence & image processingArtificial intelligencePsychologybusinessOther Computer and Information SciencecomputerCognitive psychologySocial behavior

description

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. QC 20140117

yearjournalcountryeditionlanguage
2013-06-012013 IEEE Conference on Computer Vision and Pattern Recognition
https://doi.org/10.1109/cvpr.2013.438