Idiap Poster Data

The Idiap Poster Data consists of images extracted from 6 hours of videos shot during a poster session.

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Idiap Poster Data is video dataset. The videos were shot during a real social event of over 50 people who met to present scientific work during a poster session.  Only parts of the poster session has been recorded. Around 6 hours of data have been recorded overall. The data was recorded from 2 top-down cameras that were each recording half of the scene simultaneously. The cameras are placed approximately 15 meters away from the participants of the event. The event consisted of a setting up period, coffee break, poster session, and taking down the posters at the end. The conversations that are formed were all natural and unscripted, motivated only by each individual’s real relationships with other people at the event. The data captures interactive behaviour between people who are closely acquainted (e.g. work colleagues or friends), as well as strangers.

It shows various different types of activities such as putting up posters, presenting posters, chatting, and getting tea and coffee.

The distance and orientation of the camera helps to conserve the privacy of the participants while enabling the analysis of a crowded scene. All frontal or semi-frontal faces have been blurred.

Format of the Data

The video has been extracted into frames and put into several folders. There were two cameras (A, which shot the left part of the scene and B, which shot the right part). The data was recorded with tape and since the tapes needed to be changed half way, the scene might have shifted a bit.  For each camera, there are three consecutive parts. For example, CamA_part1_003 is the folder that contains image frames that follow from CamA_part1_002. Part 2 tends to be more crowded while parts 1 and 3 are more sparse.


If you use this data, please cite the following publication

H. Hung and B. Krose, "Detecting F-formations as Dominant Sets", in International Conference on Multimodal Interaction, Alicante, Spain, November 2011.