Papers › RHM: Robot House Multi-view Human Activity Recognition Dataset
RHM: Robot House Multi-view Human Activity Recognition Dataset
Mohammad Hossein Bamorovat Abadi, Mohamad Reza Shahabian Alashti, Patrick Holthaus, Catherine Menon, Farshid Amirabdollahian
With the recent increased development of deep neural networks and dataset capabilities, the Human Action Recognition (HAR) domain is growing rapidly in terms of both the available datasets and deep models. Despite this, there are some lacks of datasets specifically covering the Robotics field and Human-Robot interaction. We prepare and introduce a new multi-view dataset to address this. The Robot House Multi-View (RHM) dataset contains four views: Front, Back, Ceiling (Omni), and robot-views. There are 14 classes with 6701 video clips for each view, making a total of 26804 video clips for the four views. The lengths of the video clips are between 1 to 5 seconds. The videos with the same number and the same classes are synchronized in different views. In the second part of this paper, we consider how single streams afford activity recognition using established state-of-the-art models. We then assess the affordance for each view based on information theoretic modelling and mutual information concept. Furthermore, we benchmark the performance of different views, thus establishing the strengths and weaknesses of each view relevant to their information content and performance of the benchmark. Our results lead us to conclude that multi-view and multi-stream activity recognition has the added potential to improve activity recognition results. The RHM dataset is available at {href{https://robothouse-dev.herts.ac.uk/datasets/RHM/HAR-1/}{Robot House}}.
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Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Human Activity Recognition | RHM | C3D | Accuracy (Top-1) | 70.3 | #2 of 4 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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