To facilitate interaction with documents in interactive tabletop applications, we explore how the orientation of documents supports efficient reading and writing. In this paper, the orientation of paper documents is systematically investigated in five different experiments. In the first three experiments, 36 Japanese participants, 18 left- and 18 right-handed, explored preferred document orientation for reading horizontal Japanese texts. Experiments 1 and 2 showed that the participants preferred to rotate text documents clockwise if left-handed and counter-clockwise if right-handed relative to their median line. On average, they rotated text documents more when annotating (about 10°) than when reading (about 5°). The difference in document rotation can be explained by the fact that text documents are rotated to facilitate hand manipulation, because they are rotated more when finer hand motions are required. No difference in document angle was found between Japanese horizontal texts and English texts (Experiment 3). In the fourth experiment, we found that right-handed people read text documents faster when they were rotated between –10° and 20° counter-clockwise. Finally, the last experiment explored the effect of document orientation on the performance of transcribing texts. The participants transcribed texts faster when documents were rotated 10° counter-clockwise. In light of the results from these paper-based experiments, we give guidelines for how to present text documents in tabletop applications depending on tasks, documents, and users.

In this paper we examine the affective content of meeting videos. First we asked five subjects to manually label three meeting videos using continuous response measurement (continuous-scale labeling in real-time) for energy and valence (the two dimensions of the human affect space). Then we automatically extracted audio-visual features to characterize the affective content of the videos. We compare the results of manual labeling and low-level automatic audio-visual feature extraction. Our analysis yields promising results, which suggest that affective meeting video analysis can lead to very interesting observations useful for automatic indexing.

We present a system based on a new, memory-cue paradigm for retrieving meeting video scenes. The system graically represents important memory retrieval cues such as room layout, participant's faces and sitting positions, etc.. Queries are formulated dynamically: as the user graically manipulates the cues, the query results are shown. Our system (1) helps users easily express the cues they recall about a particular meeting; (2) helps users remember new cues for meeting video retrieval. We discuss the experiments that motivate this new approach, implementation, and future work.