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In the last couple of years more and more multimodal corpora have been created. Recently many of these corpora have also included RGB-D sensors' data. However, there is to our knowledge no publicly available corpus, which combines accurate gaze-tracking, and high-quality audio recording for group discussions of varying dynamics. With a corpus that would fulfill these needs, it would be possible to investigate higher level constructs such as group involvement, individual engagement or rapport which all require multi-modal feature extraction. In the following paper we describe the design and recording of such a corpus and we provide some illustrative examples of how such a corpus might be exploited in the study of group dynamics.
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Stored only when both papers are in the corpus — 24 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.