Comparing Models of Disengagement in Individual and Group Interactions

Leite, Iolanda; McCoy, Marissa; Ullman, Daniel; Salomons, Nicole; Scassellati, Brian

doi:10.1145/2696454.2696466

Cited by 70 publications

(78 citation statements)

References 18 publications

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“…In [29], hand-coded features such as speech, gaze, gesture, and postures of two children were utilised to model individual and grouplevel engagement. Their F-score based feature ranking showed that gaze-related features were more discriminative than other features (e.g.…”

Section: Related Workmentioning

confidence: 99%

“…While the HRI studies [4,29] revealed that gaze-oriented movements and hand gestures were related to engagement, the settings often had regulations on behaviours of subjects or relied on hand-coded features. Without any regulation, the automatic extraction of these features is limited in naturalistic settings.…”

Section: Related Workmentioning

confidence: 99%

“…Moreover, we do not have prior knowledge of the proper size of a window for feature extraction in our study. In previous work [29,33,25], windows of between 0.5s and 5min long were used to predict engagement and dominance. To decide an optimal length of windows for detection experiments, we investigated the effect of different window length varying: {5s, 10s, 15s, 20s, and 25s}.…”

Section: Feature Analysismentioning

confidence: 99%

“…gaze, blinking, gesture) which have semantic information for engagement [1]. While these features were widely used in controlled or laboratory settings [29,4,6], we should investigate rigorous methods to extract these features in naturalistic settings where we cannot regulate children's behaviours.…”

Section: Limitations and Future Workmentioning

confidence: 99%

“…The automatic analysis and detection of engagement have been studied before using multi-modal cues such as speech activity, gaze, posture, and gestures [29,6,19,21,4]. These features can be categorised into vocal and visual features, and each category has its own strengths and drawbacks in the wild.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Multimodal Detection of Engagement in Groups of Children Using Rank Learning

Kim¹,

Truong²,

Charisi³

et al. 2016

Human Behavior Understanding

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Abstract. In collaborative play, children exhibit different levels of engagement. Some children are engaged with other children while some play alone. In this study, we investigated multimodal detection of individual levels of engagement using a ranking method and non-verbal features: turn-taking and body movement. Firstly, we automatically extracted turn-taking and body movement features in naturalistic and challenging settings. Secondly, we used an ordinal annotation scheme and employed a ranking method considering the great heterogeneity and temporal dynamics of engagement that exist in interactions. We showed that levels of engagement can be characterised by relative levels between children. In particular, a ranking method, Ranking SVM, outperformed a conventional method, SVM classification. While either turn-taking or body movement features alone did not achieve promising results, combining the two features yielded significant error reduction, showing their complementary power.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%